{ "benchmarks": { "cells_split": {}, "consensus_brier_by_horizon": { "1d": { "brier": 0.2634, "coin": 0.25, "models_mean": 0.2653, "n": 34, "n_eff": 1.79, "n_eff_per_run": [ { "indicators": 11, "n_eff": 1.72, "rho": 0.51, "run": "2026-10-19-am", "seats": 7 }, { "indicators": 12, "n_eff": 1.46, "rho": 0.64, "run": "2026-10-20-am", "seats": 8 }, { "indicators": 11, "n_eff": 2.2, "rho": 0.386, "run": "2026-10-21-am", "seats": 9 } ], "n_eff_runs": 3, "n_eff_seats": 8.0, "n_eff_why_null": null, "n_probs": 270, "rho": 0.512 } }, "late_seats": [ "meta" ], "n_eff_note": "n_probs = the probabilities that entered the consensus; rho = the mean pairwise correlation of the models' probabilities across the indicators of a run (mean over the runs); n_eff = n/(1+(n-1)rho) the effective voices (an estimate from the correlation of the errors), mean over the runs (null when no run has 3+ models in 4+ indicators); the same cells as the Brier", "n_late_excluded": 1, "rule": { "from": "2026-10-21", "rule": "A consensus cell (run, asset, horizon) holds only the rows of the issue's one event (same_event true in council-forecasts.csv); an answer on its own reference price is a different event and is left out. A cell whose rows still disagree on the outcome (up vs down) is not averaged and is counted in cells_split. Before this date the block mixed own-reference answers into the cell and took the outcome of its first row; every session is now recounted by this rule (the block is an aggregate, no day's sealed score changes)." }, "what": "Brier of the mean stated probability of the models per asset and session, by horizon, on the issue's one event only; coin = 0.25; models_mean = the mean Brier of the single models on the same cells" }, "brier": { "coin": 0.25, "council": { "brier": 0.2629, "brier_all_rows": { "brier": 0.2277, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2785, "lo": 0.2491 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2277, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "hit_ci": null, "hit_rate": 0.375, "hits": 12, "n": 34, "n_resolved": 32, "sessions": 3, "vs_coin": null }, "counted_50_note": "seats[*].brier is the stated forecasts only (a gap counted as 50% is not in it); the gaps counted as 50% (№112) are in the league's Brier, league_brier[*], where counted_50 stands beside it; horizons: score_h `nm` is counted apart in counted_50.horizons", "counted_50_total": 0, "draw_band": { "brier_events": { "brier": "the event \"up\" with draws left out — the second figure; the only one for the days published before 2026-10-21 (not recounted)", "brier_all_rows": "the event \"close above the reference price (move > 0)\" on EVERY row, a draw included, with its true sign; the MAIN Brier for the sessions from 2026-10-21 (field `pall` of the score line)" }, "draw": "|move| < band is a draw", "estimator": "the mean absolute one-minute return (in %) over the minute bars before the reference price; x sqrt(390) scales a minute to a 390-minute session", "formula": "band_% = k x mean(|1-minute return|, %) x sqrt(390)", "in_score_line": "rows[*].1d.noise (the band, %), rows[*].1d.draw", "k": 0.1, "k_config_key": "thresholds.noise_sigma", "longer_horizons": { "N": { "1d": 1, "1m": 21, "1w": 5, "6m": 126 }, "N_btc_days": { "1d": 1, "1m": 30, "1w": 7, "6m": 182 }, "estimator": "the mean absolute close-to-close return of the last 60 New York days before the reference price (hourly bars, the last hourly close of each day), a session that holds a recorded change of contract left out; N = the horizon's sessions, BTC the horizon's calendar days", "formula": "band_% = k x mean(|daily return|, %) x sqrt(N)", "note": "a different estimator from the day's (daily closes, not minutes); score_h lines carry the band as `noise`" }, "rolls": "futures: the minute moves across a recorded change of contract (its hour and the one before) are left out (№144)", "what_it_is": "k times a scale of a day's move taken from the minute bars: mean(|1-minute return|) x sqrt(390) is about 0.8 of the day's standard deviation for normal returns, so the band is about 0.08 sigma_day (k is a factor, not a sigma)", "window": "FIXED: the last 4 x 390 minute bars strictly before the reference price (4 sessions of minutes); under 100 minute moves there is no band (a late rescore keeps the run's first one)" }, "draw_band_inputs": { "formula": "band_% = k x mean(|1-minute return|, %) x sqrt(390); |move| < band is a draw", "k": 0.1, "k_source": "thresholds.noise_sigma of the settings now", "sessions": { "2026-10-19": { "book_line": 94, "markets": { "BRENT": { "band_pct": 0.1035, "draw": false, "mean_abs_1m_return_pct": 0.0524, "move_pct": 1.494 }, "BTC": { "band_pct": 0.0584, "draw": false, "mean_abs_1m_return_pct": 0.0296, "move_pct": -0.924 }, "COPPER": { "band_pct": 0.0447, "draw": false, "mean_abs_1m_return_pct": 0.0226, "move_pct": 0.251 }, "DJI": { "band_pct": 0.0416, "draw": true, "mean_abs_1m_return_pct": 0.0211, "move_pct": 0.034 }, "DXY": { "band_pct": 0.0122, "draw": false, "mean_abs_1m_return_pct": 0.0062, "move_pct": 0.145 }, "GOLD": { "band_pct": 0.0414, "draw": false, "mean_abs_1m_return_pct": 0.021, "move_pct": -0.493 }, "NDX": { "band_pct": 0.0666, "draw": false, "mean_abs_1m_return_pct": 0.0337, "move_pct": -0.149 }, "SOX": { "band_pct": 0.1493, "draw": false, "mean_abs_1m_return_pct": 0.0756, "move_pct": -1.55 }, "SPX": { "band_pct": 0.0395, "draw": false, "mean_abs_1m_return_pct": 0.02, "move_pct": -0.125 }, "US10Y": { "band_pct": 0.0729, "draw": false, "mean_abs_1m_return_pct": 0.0369, "move_pct": 0.588 }, "VIX": { "band_pct": 0.3792, "draw": false, "mean_abs_1m_return_pct": 0.192, "move_pct": 2.884 }, "WTI": { "band_pct": 0.0858, "draw": false, "mean_abs_1m_return_pct": 0.0434, "move_pct": 1.151 } }, "run_id": "2026-10-19-am" }, "2026-10-20": { "book_line": 184, "markets": { "BRENT": { "band_pct": 0.1009, "draw": false, "mean_abs_1m_return_pct": 0.0511, "move_pct": -0.935 }, "BTC": { "band_pct": 0.0648, "draw": false, "mean_abs_1m_return_pct": 0.0328, "move_pct": 1.302 }, "COPPER": { "band_pct": 0.0444, "draw": false, "mean_abs_1m_return_pct": 0.0225, "move_pct": 0.593 }, "DJI": { "band_pct": 0.0407, "draw": false, "mean_abs_1m_return_pct": 0.0206, "move_pct": 1.005 }, "DXY": { "band_pct": 0.01, "draw": false, "mean_abs_1m_return_pct": 0.0051, "move_pct": -0.019 }, "GOLD": { "band_pct": 0.0393, "draw": false, "mean_abs_1m_return_pct": 0.0199, "move_pct": 0.07 }, "NDX": { "band_pct": 0.0714, "draw": false, "mean_abs_1m_return_pct": 0.0362, "move_pct": 0.406 }, "SOX": { "band_pct": 0.1519, "draw": false, "mean_abs_1m_return_pct": 0.0769, "move_pct": 1.128 }, "SPX": { "band_pct": 0.0425, "draw": false, "mean_abs_1m_return_pct": 0.0215, "move_pct": 0.46 }, "US10Y": { "band_pct": 0.0731, "draw": false, "mean_abs_1m_return_pct": 0.037, "move_pct": 0.215 }, "VIX": { "band_pct": 0.4116, "draw": false, "mean_abs_1m_return_pct": 0.2084, "move_pct": -6.488 }, "WTI": { "band_pct": 0.0933, "draw": false, "mean_abs_1m_return_pct": 0.0472, "move_pct": -1.167 } }, "run_id": "2026-10-20-am" }, "2026-10-21": { "book_line": 234, "markets": { "BRENT": { "band_pct": 0.1054, "draw": false, "mean_abs_1m_return_pct": 0.0534, "move_pct": 1.265 }, "BTC": { "band_pct": 0.0668, "draw": false, "mean_abs_1m_return_pct": 0.0338, "move_pct": 1.062 }, "COPPER": { "band_pct": 0.0492, "draw": false, "mean_abs_1m_return_pct": 0.0249, "move_pct": 0.313 }, "DJI": { "band_pct": 0.0398, "draw": false, "mean_abs_1m_return_pct": 0.0202, "move_pct": 0.535 }, "DXY": { "band_pct": 0.0096, "draw": true, "mean_abs_1m_return_pct": 0.0049, "move_pct": 0.0 }, "GOLD": { "band_pct": 0.0388, "draw": false, "mean_abs_1m_return_pct": 0.0196, "move_pct": -0.041 }, "NDX": { "band_pct": 0.0688, "draw": false, "mean_abs_1m_return_pct": 0.0348, "move_pct": 0.396 }, "SOX": { "band_pct": 0.1484, "draw": false, "mean_abs_1m_return_pct": 0.0751, "move_pct": -0.181 }, "SPX": { "band_pct": 0.0416, "draw": false, "mean_abs_1m_return_pct": 0.0211, "move_pct": 0.312 }, "US10Y": { "band_pct": 0.0634, "draw": false, "mean_abs_1m_return_pct": 0.0321, "move_pct": 0.902 }, "VIX": { "band_pct": 0.2396, "draw": false, "mean_abs_1m_return_pct": 0.1213, "move_pct": -1.756 }, "WTI": { "band_pct": 0.0995, "draw": false, "mean_abs_1m_return_pct": 0.0504, "move_pct": 0.483 } }, "run_id": "2026-10-21-am" } }, "sigma": "mean absolute one-minute return, in %, over the last 4 x 390 minute bars strictly before the reference price (fewer than 100 moves: no band); the minute moves across a recorded change of futures contract (its hour and the one before) are left out (№144); when a late rescore has too few bars the run's first band holds, and with no moves at all the band is 0 (council_score.py)", "sigma_here": "mean_abs_1m_return_pct = band_pct / (k x sqrt(390)); the minute bars themselves are not published", "sqrt_390": 19.748418, "threshold": "band_pct, the `noise` of rows[*].1d in the score line of council-book.jsonl (book_line); a move inside it is a draw" }, "late_seats": [ "meta" ], "league_brier": { "chatgpt": { "brier": 0.2683, "counted_50": 0, "n": 34, "right": 12 }, "claude": { "brier": 0.2622, "counted_50": 0, "n": 30, "right": 9 }, "deepseek": { "brier": 0.25, "counted_50": 0, "n": 32, "right": 16 }, "gemini": { "brier": 0.2667, "counted_50": 0, "n": 34, "right": 17 }, "grok": { "brier": 0.2474, "counted_50": 0, "n": 30, "right": 14 }, "kimi": { "brier": 0.2986, "counted_50": 0, "n": 11, "right": 2 }, "meta": { "brier": 0.2124, "counted_50": 0, "n": 18, "right": 11 }, "mimo": { "brier": 0.2884, "counted_50": 0, "n": 32, "right": 11 }, "stepfun": { "brier": 0.256, "counted_50": 0, "n": 20, "right": 9 }, "wenxin": { "brier": 0.3203, "counted_50": 0, "n": 11, "right": 3 }, "zai": { "brier": 0.2302, "counted_50": 0, "n": 10, "right": 6 } }, "level": 0.95, "n_late_excluded": 1, "resamples": 2000, "seats": { "chatgpt": { "brier": 0.2683, "brier_all_rows": { "brier": 0.2425, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2847, "lo": 0.2522 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2425, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.3529, "hits": 12, "n": 34, "n_resolved": 34, "sessions": 3, "vs_coin": null }, "claude": { "brier": 0.2639, "brier_all_rows": { "brier": 0.2448, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2752, "lo": 0.2516 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2448, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.3, "hits": 9, "n": 30, "n_resolved": 30, "sessions": 3, "vs_coin": null }, "deepseek": { "brier": 0.25, "brier_all_rows": { "brier": 0.2188, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2677, "lo": 0.2329 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2188, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.5, "hits": 16, "n": 32, "n_resolved": 32, "sessions": 3, "vs_coin": null }, "gemini": { "brier": 0.2667, "brier_all_rows": { "brier": 0.236, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2925, "lo": 0.2429 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.236, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.5, "hits": 17, "n": 34, "n_resolved": 34, "sessions": 3, "vs_coin": null }, "grok": { "brier": 0.247, "brier_all_rows": { "brier": 0.2027, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2697, "lo": 0.2231 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2027, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.4667, "hits": 14, "n": 30, "n_resolved": 30, "sessions": 3, "vs_coin": null }, "kimi": { "brier": 0.2986, "brier_all_rows": null, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.3349, "lo": 0.2644 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "no_draws", "brier": 0.2986, "brier_ci": null, "event": "up, draws left out — the published days (before 2026-10-21) stand as published", "n": 11, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.1818, "hits": 2, "n": 11, "n_resolved": 11, "sessions": 1, "vs_coin": null }, "meta": { "brier": 0.2124, "brier_all_rows": { "brier": 0.2007, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 11, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2429, "lo": 0.1783 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2007, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 11, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.6111, "hits": 11, "n": 18, "n_resolved": 18, "sessions": 2, "vs_coin": null }, "mimo": { "brier": 0.2896, "brier_all_rows": { "brier": 0.2391, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.3168, "lo": 0.2667 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2391, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.3438, "hits": 11, "n": 32, "n_resolved": 32, "sessions": 3, "vs_coin": null }, "nemotron": { "brier": null, "brier_ci": null, "counted_50": 0, "n": 0, "reason": "no readable probabilities in the scored sessions", "sessions": 0 }, "nova": { "brier": null, "brier_ci": null, "counted_50": 0, "n": 0, "reason": "no readable probabilities in the scored sessions", "sessions": 0 }, "qwen": { "brier": null, "brier_ci": null, "counted_50": 0, "n": 0, "reason": "no readable probabilities in the scored sessions", "sessions": 0 }, "stepfun": { "brier": 0.2569, "brier_all_rows": { "brier": 0.2315, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2764, "lo": 0.2352 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2315, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.45, "hits": 9, "n": 20, "n_resolved": 20, "sessions": 2, "vs_coin": null }, "wenxin": { "brier": 0.3267, "brier_all_rows": null, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.3822, "lo": 0.2717 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "no_draws", "brier": 0.3267, "brier_ci": null, "event": "up, draws left out — the published days (before 2026-10-21) stand as published", "n": 11, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.2727, "hits": 3, "n": 11, "n_resolved": 11, "sessions": 1, "vs_coin": null }, "zai": { "brier": 0.2282, "brier_all_rows": { "brier": 0.2335, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "brier_ci": null, "brier_ci_by_forecast": { "hi": 0.2594, "lo": 0.2004 }, "brier_event": "up, draws left out (published days as they are) — the second figure from 2026-10-21", "brier_main": { "basis": "all_rows", "brier": 0.2335, "brier_ci": null, "event": "close above the reference price (move > 0), every row, a draw included", "from_session": "2026-10-21", "n": 12, "sessions": 1 }, "ci_from_sessions": 5, "counted_50": 0, "hit_ci": null, "hit_rate": 0.6, "hits": 6, "n": 10, "n_resolved": 10, "sessions": 1, "vs_coin": null } }, "unit": "session" }, "cells": { "definitions": { "brier_conditional": "UNCHANGED number, as published: Brier of the cells where the model gave a probability other than 50 (cell_status elicited); an explicit 50 is NOT in it. Same number as brier_conditional_ex50 (the name that says it). n_conditional.", "brier_conditional_ex50": "Brier of the elicited cells (a probability other than 50); = brier_conditional.", "brier_conditional_stated": "NEW (2026-10-21), the conditional Brier by the article's definition: Brier over EVERY stated probability, an explicit 50 included (elicited + explicit_50); = brier_with_explicit_50. n_conditional_stated. Gaps are not in it.", "brier_service": "UNCHANGED number, as published: the stated cells and the gaps the league counted as 50 (imputed_50) at 0.25; a miss, an invalid cell and a no_line cell are NOT in it. n_service.", "brier_service_all_missing": "NEW (2026-10-21): the service Brier by the article's definition: the stated cells, plus EVERY asked cell with no stated probability (imputed_50, miss, invalid, no_line) whose event resolved (no draw), each at 0.25. n_service_all_missing.", "brier_with_explicit_50": "UNCHANGED: = brier_conditional_stated.", "coverage": "cells with a stated probability (elicited + explicit_50) / cells asked.", "note": "No published number was changed: each new definition is a new field beside the old one; a page that shows brier_conditional / brier_service shows the old definitions.", "since": "2026-10-21" }, "late_seats": [ "meta" ], "method": "№332: brier_conditional = Brier of the cells where the model gave a probability other than 50 (cell_status elicited); coverage = cells with a stated probability (elicited + explicit_50) / cells asked; brier_service = the stated cells and the gaps the score counted as 50 (imputed_50); a stated 50 (explicit_50), a miss, an invalid cell and an imputed 50 are different counters - never one; portfolio = the seat's account from the league, apart from every Brier; draws and cells without an outcome yet are out of the Brier, not out of coverage; №416 (from 2026-10-21, the first day of the sealed asks book): the cells asked are the run's cells for every seat the question was SENT to (asks.jsonl), so a seat sent the question with no answer line at all counts in `asked` as `no_line` (apart from miss); earlier runs have no sealed sends and keep the coverage of their answer rows; №450 (from 2026-10-21, the same sealed sends): the run's asset x horizon grid and whether it trades its session come from its sealed question (issue.json) and run data, never from the answers - a run sent to seats and answered by none stays in the denominator", "n_late_excluded": 1, "sample_flow": { "by_horizon": { "1d": { "answered": 408, "asked": 480, "counted": 296, "dropped": { "answered->valid": 3, "asked->answered": 72, "counted->resolved": 17, "valid->counted": 109 }, "dropped_by_reason": { "answered->valid": { "invalid": 3 }, "asked->answered": { "no_line": 72 }, "counted->resolved": { "draw": 17 }, "valid->counted": { "no_outcome_yet": 109 } }, "resolved": 279, "valid": 405 }, "1m": { "answered": 408, "asked": 480, "counted": 0, "dropped": { "answered->valid": 3, "asked->answered": 72, "counted->resolved": 0, "valid->counted": 405 }, "dropped_by_reason": { "answered->valid": { "invalid": 3 }, "asked->answered": { "no_line": 72 }, "valid->counted": { "no_outcome_yet": 405 } }, "resolved": 0, "valid": 405 }, "1w": { "answered": 408, "asked": 480, "counted": 0, "dropped": { "answered->valid": 3, "asked->answered": 72, "counted->resolved": 0, "valid->counted": 405 }, "dropped_by_reason": { "answered->valid": { "invalid": 3 }, "asked->answered": { "no_line": 72 }, "valid->counted": { "no_outcome_yet": 405 } }, "resolved": 0, "valid": 405 }, "6m": { "answered": 408, "asked": 480, "counted": 0, "dropped": { "answered->valid": 3, "asked->answered": 72, "counted->resolved": 0, "valid->counted": 405 }, "dropped_by_reason": { "answered->valid": { "invalid": 3 }, "asked->answered": { "no_line": 72 }, "valid->counted": { "no_outcome_yet": 405 } }, "resolved": 0, "valid": 405 } }, "by_run": { "2026-10-19-am": { "answered": 336, "asked": 336, "counted": 83, "dropped_by_reason": { "counted->resolved": { "draw": 7 }, "valid->counted": { "no_outcome_yet": 253 } }, "resolved": 76, "valid": 336 }, "2026-10-20-am": { "answered": 432, "asked": 432, "counted": 105, "dropped_by_reason": { "answered->valid": { "invalid": 12 }, "counted->resolved": { "draw": 1 }, "valid->counted": { "no_outcome_yet": 315 } }, "resolved": 104, "valid": 420 }, "2026-10-21-am": { "answered": 432, "asked": 480, "counted": 108, "dropped_by_reason": { "asked->answered": { "no_line": 48 }, "counted->resolved": { "draw": 9 }, "valid->counted": { "no_outcome_yet": 324 } }, "resolved": 99, "valid": 432 }, "2026-10-22-am": { "answered": 432, "asked": 672, "counted": 0, "dropped_by_reason": { "asked->answered": { "no_line": 240 }, "valid->counted": { "no_outcome_yet": 432 } }, "resolved": 0, "valid": 432 } }, "reasons": "no_line = sent, no answer line; miss / invalid / imputed_50 = a line, no stated probability; no_outcome_yet = the horizon is not closed (the outcome is not in); excluded = the outcome is in but the score left the cell out (not_counted); draw = a move inside the draw band, out of the event Brier", "rule": "asked = the cells of the runs that trade their session, for every seat the question was sent to (no_line = sent, no answer line); answered = a line came; valid = a stated probability (a miss, an invalid cell and an imputed 50 are not); counted = valid and counted by the score; resolved = counted with the outcome in and not a draw - the cells of the Brier. Each step is a subset of the one before", "steps": [ "asked", "answered", "valid", "counted", "resolved" ], "total": { "answered": 1632, "asked": 1920, "counted": 296, "dropped": { "answered->valid": 12, "asked->answered": 288, "counted->resolved": 17, "valid->counted": 1324 }, "dropped_by_reason": { "answered->valid": { "invalid": 12 }, "asked->answered": { "no_line": 288 }, "counted->resolved": { "draw": 17 }, "valid->counted": { "no_outcome_yet": 1324 } }, "resolved": 279, "valid": 1620 } }, "seats": { "chatgpt": { "horizons": { "1d": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 34, "values": [ 0.2683, 0.2683 ] }, "brier_conditional": 0.2683, "brier_conditional_ex50": 0.2683, "brier_conditional_stated": 0.2683, "brier_service": 0.2683, "brier_service_all_missing": 0.2683, "brier_with_explicit_50": 0.2683, "common_events": 34, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 48, "explicit_50": 0, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": 0.2683, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 34, "n_conditional_stated": 34, "n_service": 34, "n_service_all_missing": 34, "no_line": 0, "stated": 48 }, "1m": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 48, "explicit_50": 0, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 }, "1w": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 48, "explicit_50": 0, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 }, "6m": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 48, "explicit_50": 0, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 } }, "portfolio": { "hold_ret_pct": null, "ret_pct": -0.042, "sp500_ret_pct": 0.714, "value": 99958.12 } }, "claude": { "horizons": { "1d": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 34, "values": [ 0.2622, 0.2622 ] }, "brier_conditional": 0.2639, "brier_conditional_ex50": 0.2639, "brier_conditional_stated": 0.2622, "brier_service": 0.2622, "brier_service_all_missing": 0.2622, "brier_with_explicit_50": 0.2622, "common_events": 34, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 43, "explicit_50": 5, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": 0.2622, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 30, "n_conditional_stated": 34, "n_service": 34, "n_service_all_missing": 34, "no_line": 0, "stated": 48 }, "1m": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 48, "explicit_50": 0, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 }, "1w": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 39, "explicit_50": 9, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 }, "6m": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 48, "explicit_50": 0, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 } }, "portfolio": { "hold_ret_pct": null, "ret_pct": 0.266, "sp500_ret_pct": 0.714, "value": 100265.54 } }, "deepseek": { "horizons": { "1d": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 34, "values": [ 0.25, 0.25 ] }, "brier_conditional": 0.25, "brier_conditional_ex50": 0.25, "brier_conditional_stated": 0.25, "brier_service": 0.25, "brier_service_all_missing": 0.25, "brier_with_explicit_50": 0.25, "common_events": 34, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 45, "explicit_50": 3, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": 0.25, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 32, "n_conditional_stated": 34, "n_service": 34, "n_service_all_missing": 34, "no_line": 0, "stated": 48 }, "1m": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 45, "explicit_50": 3, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 }, "1w": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 46, "explicit_50": 2, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 }, "6m": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 47, "explicit_50": 1, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 } }, "portfolio": { "hold_ret_pct": null, "ret_pct": -0.185, "sp500_ret_pct": 0.714, "value": 99814.7 } }, "gemini": { "horizons": { "1d": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 34, "values": [ 0.2667, 0.2667 ] }, "brier_conditional": 0.2667, "brier_conditional_ex50": 0.2667, "brier_conditional_stated": 0.2667, "brier_service": 0.2667, "brier_service_all_missing": 0.2667, "brier_with_explicit_50": 0.2667, "common_events": 34, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 47, "explicit_50": 1, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": 0.2667, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 34, "n_conditional_stated": 34, "n_service": 34, "n_service_all_missing": 34, "no_line": 0, "stated": 48 }, "1m": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 47, "explicit_50": 1, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 48 }, "1w": { "asked": 48, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 48, "explicit_50": 0, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; 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brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 24 }, "6m": { "asked": 24, "brier_bounds": { "missing_as": [ 0, 1 ], "n_missing": 0, "n_stated": 0, "values": [ null, null ] }, "brier_conditional": null, "brier_conditional_ex50": null, "brier_conditional_stated": null, "brier_service": null, "brier_service_all_missing": null, "brier_with_explicit_50": null, "common_events": 0, "common_events_rule": "events (run, asset) of this horizon where this seat and at least one other seat stated a probability, i.e. where the consensus of the others exists", "coverage": 1.0, "elicited": 22, "explicit_50": 2, "imputed_50": 0, "invalid": 0, "league_fill": { "brier_service": null, "cells": 0, "rule": "a gap inside an answer that gave forecasts is counted as 50 (Brier 0.25) by the league; brier_service = stated + these", "value": 0.25 }, "miss": 0, "n_conditional": 0, "n_conditional_stated": 0, "n_service": 0, "n_service_all_missing": 0, "no_line": 0, "stated": 24 } }, "portfolio": { "hold_ret_pct": null, "ret_pct": 0.062, "sp500_ret_pct": 0.714, "value": 100061.68 } } } }, "corrections": { "cells_from_correction_lines": 103, "csv_columns": [ "line_kind (issue | correction)", "sealed_at" ], "rule": "one rule: a cell given by a line of kind `correction` (council-forecasts.csv: line_kind, sealed_at = the seal time of that line) is NOT in the published days (their score and every number here stand as published); a horizon closed after its sealed_at counts it, apart (nr); every other cell counts by its status (counted, counted_50)" }, "crowd_floor_usd": 1000, "data_as_of": "2026-10-22T16:19:01Z", "data_through_session": "2026-10-21", "estimators": { "before_roster_change": { "from": "2026-10-21", "seats": { "chatgpt": { "cells": 11, "delta_ci": null, "delta_if_removed": -0.0025, "paired_loss_with": 0.2229, "paired_loss_without": 0.2204, "ready": false, "sessions": 1 }, "claude": { "cells": 11, "delta_ci": null, "delta_if_removed": -0.0024, "paired_loss_with": 0.2229, "paired_loss_without": 0.2205, "ready": false, "sessions": 1 }, "deepseek": { "cells": 11, "delta_ci": null, "delta_if_removed": 0.0014, "paired_loss_with": 0.2229, "paired_loss_without": 0.2243, "ready": false, "sessions": 1 }, "gemini": { "cells": 11, "delta_ci": null, "delta_if_removed": -0.0004, "paired_loss_with": 0.2229, "paired_loss_without": 0.2225, "ready": false, "sessions": 1 }, "grok": { "cells": 11, "delta_ci": null, "delta_if_removed": 0.0029, "paired_loss_with": 0.2229, "paired_loss_without": 0.2258, "ready": false, "sessions": 1 }, "meta": { "cells": 10, "delta_ci": null, "delta_if_removed": 0.0046, "paired_loss_with": 0.2232, "paired_loss_without": 0.2278, "ready": false, "sessions": 1 }, "mimo": { "cells": 11, "delta_ci": null, "delta_if_removed": -0.0014, "paired_loss_with": 0.2229, "paired_loss_without": 0.2215, "ready": false, "sessions": 1 }, "stepfun": { "cells": 11, "delta_ci": null, "delta_if_removed": -0.0006, "paired_loss_with": 0.2229, "paired_loss_without": 0.2223, "ready": false, "sessions": 1 }, "zai": { "cells": 11, "delta_ci": null, "delta_if_removed": -0.0008, "paired_loss_with": 0.2229, "paired_loss_without": 0.2221, "ready": false, "sessions": 1 } }, "what": "delta_if_removed = loss without the seat - loss with it (above 0: removing it would hurt the consensus); published for the window after the freeze, before any seat is added or removed (weights_freeze.seat_change)" }, "estimators": { "china": { "1d": { "ambiguity": 0.0015, "brier": 0.2714, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2729 }, "all": { "ambiguity": 0.0015, "brier": 0.2714, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2729 } }, "consensus": { "1d": { "ambiguity": 0.0019, "brier": 0.2634, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2653 }, "all": { "ambiguity": 0.0019, "brier": 0.2634, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2653 } }, "trimmed": { "1d": { "ambiguity": 0.0007, "brier": 0.2639, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2645 }, "all": { "ambiguity": 0.0007, "brier": 0.2639, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2645 } }, "usa": { "1d": { "ambiguity": 0.0019, "brier": 0.2571, "identity_gap_max": 0.0, "identity_holds": true, "n": 34, "participants_brier": 0.259 }, "all": { "ambiguity": 0.0019, "brier": 0.2571, "identity_gap_max": 0.0, "identity_holds": true, "n": 34, "participants_brier": 0.259 } }, "weighted": { "1d": { "ambiguity": 0.0019, "brier": 0.2637, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2656 }, "all": { "ambiguity": 0.0019, "brier": 0.2637, "identity_gap_max": 1e-06, "identity_holds": true, "n": 34, "participants_brier": 0.2656 } } }, "from": "2026-10-21", "frozen_ensemble": { "brier": null, "consensus_brier": null, "diff_ci": null, "from": "2026-10-22", "mean_diff": null, "n_events": 0, "prospective": true, "sessions": 0, "spec": { "families": [ [ "chatgpt", "openai" ], [ "gpt", "openai" ], [ "claude", "anthropic" ], [ "gemini", "google" ], [ "grok", "xai" ], [ "meta", "meta" ], [ "llama", "meta" ], [ "deepseek", "deepseek" ], [ "kimi", "moonshot" ], [ "mimo", "xiaomi" ], [ "stepfun", "stepfun" ], [ "wenxin", "baidu" ], [ "ernie", "baidu" ], [ "zai", "zhipu" ], [ "glm", "zhipu" ], [ "qwen", "alibaba" ], [ "mistral", "mistral" ] ], "family_match": "the first prefix that the seat id starts with wins (the order of the list)", "from": "2026-10-22", "name": "frozen_family", "scored": "prospectively: sessions from the freeze date only; the sessions before it are never scored by it", "weights": "dependence-aware: every family (lab) in the cell has one equal share, split equally inside the family; no learning, no refit, no parameter of the data - the weights are a function of the seat list and the map only" }, "spec_sha256": "62fc0d2820a3af409994f2cf4a26e1516e4f0185d32ca59215eaea52445db4dd", "why_null": "no scored session from 2026-10-22 yet (the ensemble counts prospectively only)" }, "late_seats": [ "meta" ], "leave_one_out": { "cells": 34, "cells_no_flip": 32, "models": { "chatgpt": { "cells": 34, "delta_brier_if_removed": -0.0004, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0134, "mean_shift": 0.0038 }, "claude": { "cells": 34, "delta_brier_if_removed": 0.0005, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0166, "mean_shift": 0.0045 }, "deepseek": { "cells": 34, "delta_brier_if_removed": 0.0024, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0167, "mean_shift": 0.0036 }, "gemini": { "cells": 34, "delta_brier_if_removed": 0.0001, "delta_ci": null, "direction_flips": 1, "flip_share": 0.0294, "max_shift": 0.015, "mean_shift": 0.007 }, "grok": { "cells": 34, "delta_brier_if_removed": 0.0027, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0233, "mean_shift": 0.0044 }, "kimi": { "cells": 11, "delta_brier_if_removed": -0.0025, "delta_ci": null, "direction_flips": 1, "flip_share": 0.0909, "max_shift": 0.0213, "mean_shift": 0.0048 }, "meta": { "cells": 10, "delta_brier_if_removed": 0.0046, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0174, "mean_shift": 0.0063 }, "mimo": { "cells": 33, "delta_brier_if_removed": -0.0035, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0214, "mean_shift": 0.0051 }, "stepfun": { "cells": 23, "delta_brier_if_removed": -0.0002, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0093, "mean_shift": 0.0031 }, "wenxin": { "cells": 12, "delta_brier_if_removed": -0.0048, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0209, "mean_shift": 0.0061 }, "zai": { "cells": 11, "delta_brier_if_removed": -0.0008, "delta_ci": null, "direction_flips": 0, "flip_share": 0.0, "max_shift": 0.0062, "mean_shift": 0.0024 } }, "robust_share": 0.9412, "rule": "for every cell with 3+ models the equal-mean consensus is recomputed without each model in turn; flip = the consensus crosses 50%; delta_brier_if_removed = Brier without the model - Brier with it, on the same cells (above 0: the model helps); delta_ci = its interval by whole sessions, as seat_out (null under 5 sessions)" }, "n_events": 34, "n_late_excluded": 1, "rules": { "ambiguity": "a market-session (run, asset, horizon): the mean Brier of the participants minus the Brier of the estimator's mean (weighted as the estimator is); identity checked at every event, `identity_gap_max`", "china": "the equal mean of the China-side seats", "consensus": "the equal mean of the forecasts of the cell", "family": "from 2026-10-22: every family (lab) of the models in the cell has one equal share, split equally inside the family, so one family never outweighs another (the seats of today are one a lab: it equals the equal mean until a lab has two)", "trimmed": "from 5 forecasts in a cell the highest and the lowest are dropped (one from each end), the rest averaged equally; under 5 - the plain mean", "usa": "the equal mean of the US-side seats", "weighted": "weight = the seat's hit rate on the earlier sessions (1d calls with a side, from 5 resolved calls; otherwise 0.5; at least 0.01), learned only after the session" }, "seat_out": { "seats": { "chatgpt": { "brier_with": 0.2634, "brier_without": 0.263, "cells": 34, "delta": -0.0004, "delta_ci": null, "sessions": 3 }, "claude": { "brier_with": 0.2634, "brier_without": 0.2639, "cells": 34, "delta": 0.0005, "delta_ci": null, "sessions": 3 }, "deepseek": { "brier_with": 0.2634, "brier_without": 0.2658, "cells": 34, "delta": 0.0024, "delta_ci": null, "sessions": 3 }, "gemini": { "brier_with": 0.2634, "brier_without": 0.2634, "cells": 34, "delta": 0.0001, "delta_ci": null, "sessions": 3 }, "grok": { "brier_with": 0.2634, "brier_without": 0.2661, "cells": 34, "delta": 0.0027, "delta_ci": null, "sessions": 3 }, "kimi": { "brier_with": 0.2837, "brier_without": 0.2812, "cells": 11, "delta": -0.0025, "delta_ci": null, "sessions": 1 }, "meta": { "brier_with": 0.2232, "brier_without": 0.2278, "cells": 10, "delta": 0.0046, "delta_ci": null, "sessions": 1 }, "mimo": { "brier_with": 0.2634, "brier_without": 0.2598, "cells": 33, "delta": -0.0035, "delta_ci": null, "sessions": 3 }, "stepfun": { "brier_with": 0.2536, "brier_without": 0.2535, "cells": 23, "delta": -0.0002, "delta_ci": null, "sessions": 2 }, "wenxin": { "brier_with": 0.2818, "brier_without": 0.277, "cells": 12, "delta": -0.0048, "delta_ci": null, "sessions": 1 }, "zai": { "brier_with": 0.2229, "brier_without": 0.2221, "cells": 11, "delta": -0.0008, "delta_ci": null, "sessions": 1 } }, "what": "leave-one-seat-out on the common events: the equal-mean consensus without the seat against with it on the same cells (delta > 0 - the seat lowers the consensus loss); a cell needs 3 or more seats; interval by whole sessions" }, "seat_out_after_freeze": { "events": 11, "from": "2026-10-21", "rule": "the same score as seat_out (the equal-mean consensus without the seat against with it on the same cells, 3+ seats a cell, interval by whole sessions) on the events of the sessions from the freeze of the weights; the sessions before it are not in this window", "seats": { "chatgpt": { "brier_with": 0.2229, "brier_without": 0.2204, "cells": 11, "delta": -0.0025, "delta_ci": null, "sessions": 1 }, "claude": { "brier_with": 0.2229, "brier_without": 0.2205, "cells": 11, "delta": -0.0024, "delta_ci": null, "sessions": 1 }, "deepseek": { "brier_with": 0.2229, "brier_without": 0.2243, "cells": 11, "delta": 0.0014, "delta_ci": null, "sessions": 1 }, "gemini": { "brier_with": 0.2229, "brier_without": 0.2225, "cells": 11, "delta": -0.0004, "delta_ci": null, "sessions": 1 }, "grok": { "brier_with": 0.2229, "brier_without": 0.2258, "cells": 11, "delta": 0.0029, "delta_ci": null, "sessions": 1 }, "meta": { "brier_with": 0.2232, "brier_without": 0.2278, "cells": 10, "delta": 0.0046, "delta_ci": null, "sessions": 1 }, "mimo": { "brier_with": 0.2229, "brier_without": 0.2215, "cells": 11, "delta": -0.0014, "delta_ci": null, "sessions": 1 }, "stepfun": { "brier_with": 0.2229, "brier_without": 0.2223, "cells": 11, "delta": -0.0006, "delta_ci": null, "sessions": 1 }, "zai": { "brier_with": 0.2229, "brier_without": 0.2221, "cells": 11, "delta": -0.0008, "delta_ci": null, "sessions": 1 } }, "sessions": 1 }, "us_cn_common": { "by_horizon": { "1d": { "china_brier": 0.2714, "events": 34, "usa_brier": 0.2571 } }, "china_brier": 0.2714, "coverage": { "both": 34, "china_only": 0, "events": 34, "usa_only": 0 }, "diff_ci": null, "mean_diff": -0.0142, "rule": "only the cells where at least one US-side and one China-side model answered; both sides are scored on exactly those cells", "sessions": 3, "usa_brier": 0.2571 } }, "evidence_level": { "counted": { "2026-10-19-am": "1", "2026-10-20-am": "1", "2026-10-21-am": "2+" }, "levels": [ "1", "2", "2+" ], "rule": "Table 9 of the paper: \"Order of seal and reference price ... the operator's record (level 1); the Bitcoin anchor bounds when the lines existed (level 2)\"; from 21 October 2026 two independent RFC 3161 authorities (level 2+). evidence_level_order (and evidence_level, which equals it) is the proof of the ORDER, that the answers were sealed before the reference price (09:30 ET of the session): \"2+\" = a stamped list covering the run's lines was signed by at least two independent RFC 3161 authorities before the reference; \"1\" = the seal time in the operator's hash-chained book is before the reference; null = no seal time before the reference. The Bitcoin anchor never raises the order: the paper puts P1b at \"level 1 for 19 and 20 October; level 2+ from 21 October\", and \"at level 1 the operator's record (booked_at and the prev/link chain) shows that an answer was sealed before the reference price\". evidence_level_existence is the proof that the lines existed no later than a time: \"2+\" = at least two RFC 3161 authorities, \"2\" = a Bitcoin (OpenTimestamps) anchor, \"1\" = the operator's record. For \"2\" the paper says the anchored prefix \"existed no later than the block time plus the consensus tolerance (about two hours)\": btc_time (claim-status.json, from daily/council/ots-block-times.json) is the header time of the block, not the exact moment of the block, so read it as \"no later than a few hours after\", never as \"before the block time\". All are read from external_time and print_time in claim-status.json and recomputed on every build. Rule dated 2026-10-22.", "rule_from": "2026-10-22", "runs": [ { "evidence_file": "seals/2026-10-18/085436Z.txt", "evidence_level": "1", "evidence_level_existence": "2", "evidence_level_order": "1", "role": "reference_only", "run_id": "2026-10-16-eve", "session": "2026-10-19" }, { "evidence_file": "seals/2026-10-18/093451Z.txt", "evidence_level": "1", "evidence_level_existence": "2", "evidence_level_order": "1", "role": "reference_only", "run_id": "2026-10-17-btc", "session": "2026-10-19" }, { "evidence_file": "seals/2026-10-19/012441Z.txt", "evidence_level": "1", "evidence_level_existence": "2", "evidence_level_order": "1", "role": "reference_only", "run_id": "2026-10-18-radar", "session": "2026-10-19" }, { "evidence_file": "seals/2026-10-19/132417Z.txt", "evidence_level": "1", "evidence_level_existence": "2", "evidence_level_order": "1", "role": "counted", "run_id": "2026-10-19-am", "session": "2026-10-19" }, { "evidence_file": "seals/2026-10-20/130025Z.txt", "evidence_level": "1", "evidence_level_existence": "2", "evidence_level_order": "1", "role": "counted", "run_id": "2026-10-20-am", "session": "2026-10-20" }, { "evidence_file": "seals/2026-10-21/132337Z.txt", "evidence_level": "2+", "evidence_level_existence": "2+", "evidence_level_order": "2+", "role": "counted", "run_id": "2026-10-21-am", "session": "2026-10-21" }, { "evidence_file": "seals/2026-10-22/132329Z.txt", "evidence_level": "2+", "evidence_level_existence": "2+", "evidence_level_order": "2+", "role": "reference_only", "run_id": "2026-10-22-am", "session": "2026-10-22" } ] }, "generated": "2026-10-22T17:08:36Z", "goal": { "as_of": "2026-10-21", "bss": "BSS = 1 - Brier / Brier of the reference on the same events (above 0: better than the reference). Council = the equal mean of the cell's probabilities, the issue's one event. coin = 0.25; climatology_fixed and crowd only at 1d (the crowd: the answer to the crowd's question against the contract's OWN outcome (never ours), Polymarket else Kalshi, only cells where the contract has an outcome; a model needs its own pair in the crowd line, else null).", "council": { "1d": { "climatology_fixed": { "bss": -0.0904, "interval": null, "n_eff": 9.9, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.0535, "interval": null, "n_eff": 6.4, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.3441, "interval": null, "n_eff": 19.0, "n_events": 19, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" } } }, "crowd_floor_usd": 1000, "goal": "the Council or the models beat the crowd and the references statistically", "headline": { "comparable": 18, "council_right": 13, "crowd_right": 15, "interval_from": "2026-10-23", "line": "2026-10-19 to 2026-10-21: Council's side on the crowd's questions: 13 of 18; crowd 15 of 18; 3 sessions; interval from 2026-10-23", "rule_from": "2026-10-22", "sessions": 3, "stage": "count", "window": { "from": "2026-10-19", "to": "2026-10-21" } }, "interval": "the 95% interval of the mean gain by whole sessions (weighted_interval: Student t on the cluster-robust error from 5 sessions, bootstrap from 20; under 5 sessions null), divided by the mean Brier of the reference; n_eff = events / (1 + (mean events per session - 1) rho)", "models": { "chatgpt": { "1d": { "climatology_fixed": { "bss": -0.111, "interval": null, "n_eff": 34.0, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.0734, "interval": null, "n_eff": 17.1, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.1284, "interval": null, "n_eff": 13.0, "n_events": 13, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" } } }, "claude": { "1d": { "climatology_fixed": { "bss": -0.0856, "interval": null, "n_eff": 34.0, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.0489, "interval": null, "n_eff": 8.3, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.1162, "interval": null, "n_eff": 4.5, "n_events": 13, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" } } }, "deepseek": { "1d": { "climatology_fixed": { "bss": -0.0349, "interval": null, "n_eff": 6.9, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": 0.0001, "interval": null, "n_eff": 7.0, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.2873, "interval": null, "n_eff": 13.0, "n_events": 13, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" } } }, "gemini": { "1d": { "climatology_fixed": { "bss": -0.1042, "interval": null, "n_eff": 22.4, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.0669, "interval": null, "n_eff": 18.7, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.2622, "interval": null, "n_eff": 13.0, "n_events": 13, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" } } }, "grok": { "1d": { "climatology_fixed": { "bss": -0.0242, "interval": null, "n_eff": 10.3, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": 0.0105, "interval": null, "n_eff": 8.4, "n_events": 34, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.1691, "interval": null, "n_eff": 13.0, "n_events": 13, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" } } }, "kimi": { "1d": { "climatology_fixed": { "bss": -0.0959, "interval": null, "n_eff": 11.0, "n_events": 11, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.1943, "interval": null, "n_eff": 11.0, "n_events": 11, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "crowd": null, "crowd_reason": "no contract outcomes for the models yet" } }, "meta": { "1d": { "climatology_fixed": { "bss": 0.1463, "interval": null, "n_eff": 10.0, "n_events": 10, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": 0.2335, "interval": null, "n_eff": 10.0, "n_events": 10, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.8519, "interval": null, "n_eff": 4.0, "n_events": 4, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" } } }, "mimo": { "1d": { "climatology_fixed": { "bss": -0.1964, "interval": null, "n_eff": 17.4, "n_events": 33, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.1535, "interval": null, "n_eff": 6.2, "n_events": 33, "n_sessions": 3, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.257, "interval": null, "n_eff": 13.0, "n_events": 13, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" } } }, "stepfun": { "1d": { "climatology_fixed": { "bss": -0.129, "interval": null, "n_eff": 7.1, "n_events": 23, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.024, "interval": null, "n_eff": 3.9, "n_events": 23, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.2708, "interval": null, "n_eff": 13.0, "n_events": 13, "n_sessions": 2, "verdict": "too few sessions (<5) — no verdict" } } }, "wenxin": { "1d": { "climatology_fixed": { "bss": -0.3965, "interval": null, "n_eff": 12.0, "n_events": 12, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": -0.2811, "interval": null, "n_eff": 12.0, "n_events": 12, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.2239, "interval": null, "n_eff": 8.0, "n_events": 8, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" } } }, "zai": { "1d": { "climatology_fixed": { "bss": -0.0279, "interval": null, "n_eff": 11.0, "n_events": 11, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "coin": { "bss": 0.0792, "interval": null, "n_eff": 11.0, "n_events": 11, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" }, "crowd": { "bss": -0.4469, "interval": null, "n_eff": 5.0, "n_events": 5, "n_sessions": 1, "verdict": "too few sessions (<5) — no verdict" } } } }, "primary_rule": { "check_date": "2027-04-30", "marker": "within_margin", "note": "the rule and the check date only: the primary test is read on the check date, and no running number of it is published before it", "order": "read in order: confirmed if the 95% CI is above 0; otherwise no gain of practical size if the 90% CI is inside +-0.01; otherwise inconclusive; a confirmed gain whose 90% CI is inside the zone +-0.01 is marked `within_margin`", "verdicts": [ "confirmed", "no gain of practical size", "inconclusive" ] }, "thin_market": { "below_usd": 1000, "rule": "a crowd market with a sealed turnover under crowd_floor_usd dollars is thin: it is shown with the label «thin market» and is not in the AI-vs-crowd count; the rule applies to sessions from rule_from_session, earlier sessions are never thin; no sealed volume = no verdict", "rule_from_session": "2026-10-22" }, "verdicts": [ "interval above 0", "includes 0", "below 0", "too few sessions (<5) — no verdict" ] }, "horizons": { "horizons": { "1m": { "block": 21, "brier": null, "brier_ci": null, "n": 0, "n_late_excluded": 0, "runs": 0, "seats": {} }, "1w": { "block": 5, "brier": null, "brier_ci": null, "n": 0, "n_late_excluded": 0, "runs": 0, "seats": {} }, "6m": { "block": 126, "brier": null, "brier_ci": null, "descriptive": true, "descriptive_note": "descriptive: the six-month outcomes overlap (126 sessions each) and are few, so the number is shown without an interval and is not a test of who is better", "n": 0, "n_late_excluded": 0, "runs": 0, "seats": {} } }, "method": "moving-block bootstrap over the runs in time order (one mean Brier per run from the `score_h` lines), block = the horizon's sessions (1w 5, 1m 21, 6m 126): the outcomes of neighbouring runs overlap, so single runs are never drawn; needs 2 blocks" }, "late_excluded": { "by_horizon": { "1d": 1 }, "late_cells": [ { "asset": "BTC", "horizon": "1d", "late_s": 1398, "own_ref": 83677.078125, "own_reference_at": "2026-10-21T13:23:37Z", "own_reference_bar_at": "2026-10-21T13:24:00Z", "run": "2026-10-21-am", "seat": "meta" }, { "asset": "BTC", "horizon": "1m", "late_s": 1398, "own_ref": null, "own_reference_at": "2026-10-21T13:23:37Z", "own_reference_bar_at": "2026-10-21T13:24:00Z", "run": "2026-10-21-am", "seat": "meta" }, { "asset": "BTC", "horizon": "1w", "late_s": 1398, "own_ref": null, "own_reference_at": "2026-10-21T13:23:37Z", "own_reference_bar_at": "2026-10-21T13:24:00Z", "run": "2026-10-21-am", "seat": "meta" }, { "asset": "BTC", "horizon": "6m", "late_s": 1398, "own_ref": null, "own_reference_at": "2026-10-21T13:23:37Z", "own_reference_bar_at": "2026-10-21T13:24:00Z", "run": "2026-10-21-am", "seat": "meta" } ], "late_seats": [ "meta" ], "n_late_answers": 1, "n_late_excluded": 1, "note": "Статья №9 п.92: the rows left out of this number because their answer was sealed after the reference price (late_ref: an own reference, a different event) - from 2026-10-21 (same_event) they are in no shared statistic; earlier sessions keep them, as published. n_late_excluded counts cells (answer x market), n_late_answers the answer lines, late_seats who they were; a count, not a list of who did not answer. late_cells = those cells one by one (own reference time, the 1-minute bar, the own price, late_s against the shared reference).", "sessions": 1 }, "license": "CC BY 4.0", "method_segments": { "rule": "one segment per version of the rules in force on the session's date; the Brier of a segment uses only its own sessions (interval by whole sessions, null under 5). The segments do not replace the continuous score", "versions": { "m1": { "from_session": "0000-00-00", "pairs": { "chatgpt|claude": { "a": "chatgpt", "b": "claude", "better": null, "cells": 11, "ci": null, "mean_diff": 0.0034, "sessions": 1 }, "chatgpt|deepseek": { "a": "chatgpt", "b": "deepseek", "better": null, "cells": 11, "ci": null, "mean_diff": 0.0389, "sessions": 1 }, "chatgpt|gemini": { "a": "chatgpt", "b": "gemini", "better": null, "cells": 11, "ci": null, "mean_diff": 0.0038, "sessions": 1 }, "chatgpt|grok": { "a": "chatgpt", "b": "grok", "better": null, "cells": 11, "ci": null, "mean_diff": 0.0232, "sessions": 1 }, "chatgpt|kimi": { "a": "chatgpt", "b": "kimi", "better": null, "cells": 11, "ci": null, "mean_diff": -0.0118, "sessions": 1 }, "chatgpt|mimo": { "a": "chatgpt", "b": "mimo", "better": null, "cells": 10, "ci": null, "mean_diff": -0.0611, "sessions": 1 }, "claude|deepseek": { "a": "claude", "b": "deepseek", "better": null, "cells": 11, "ci": null, "mean_diff": 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"sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.038 }, "deepseek": { "from": "2026-10-21", "return_pct": 0.359, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.166 }, "gemini": { "from": "2026-10-21", "return_pct": 0.241, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.284 }, "grok": { "from": "2026-10-21", "return_pct": 0.436, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.09 }, "kimi": { "from": "2026-10-21", "return_pct": 0.235, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.291 }, "meta": { "from": "2026-10-21", "return_pct": 0.081, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.444 }, "mimo": { "from": "2026-10-21", "return_pct": 0.687, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": 0.162 }, "nemotron": { "from": "2026-10-21", "return_pct": 0.456, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.07 }, "nova": { "from": "2026-10-21", "return_pct": 0.225, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.3 }, "qwen": { "from": "2026-10-21", "return_pct": 0.757, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": 0.232 }, "stepfun": { "from": "2026-10-21", "return_pct": 0.484, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.042 }, "wenxin": { "from": "2026-10-21", "return_pct": 0.004, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.522 }, "zai": { "from": "2026-10-21", "return_pct": 0.19, "sessions": 1, "sp500_pct": 0.525, "to": "2026-10-21", "vs_sp500": -0.335 } }, "rules": "dated rules: the Brier on every row with the draw band, one reference price per shared score (same event), Kalshi strikes, buy_dips, US10Y/VIX direction" }, "m4": { "from_session": "2026-10-22", "pairs": {}, "participants": {}, "portfolios": {}, "rules": "the dated rules of 2026-10-22: the «am» question before the open (early ask), the confirmed-bar close wording (close_bar_v2), thin crowd markets flagged, the number and sides of the AIs from the roster, rating B by sessions, score versions on every line, the dated rules crowd_line and crowd_comparison" } } }, "momentum": { "brier": 0.2616, "brier_ci": null, "hit": 0.4091, "late_seats": [ "meta" ], "n": 22, "n_late_excluded": 1, "name": "momentum", "p": 55.0, "rule": "yesterday's direction of the same indicator, at a fixed confidence", "sessions": 2, "since": "2026-10-20" }, "momentum_naive": { "beside": [ "coin (50%, Brier 0.25)", "climatology", "momentum (fixed p, kept as published)" ], "brier": 0.2486, "brier_ci": null, "chance_of_continuing": { "BRENT": 0.4917, "BTC": 0.4816, "COPPER": 0.4817, "DJI": 0.4927, "DXY": 0.4887, "GOLD": 0.4833, "NDX": 0.4972, "SOX": 0.4898, "SPX": 0.4825, "US10Y": 0.488, "VIX": 0.4852, "WTI": 0.4895 }, "hit": 0.4091, "label": "naive rule", "n": 22, "name": "momentum_naive", "note": "a fixed 55% against a fair coin has the expected Brier 0.5*0.45^2+0.5*0.55^2 = 0.2525, worse than the coin by construction", "rule": "yesterday's direction of the same indicator at the share of days that continued their direction over a FIXED window of daily closes 2006-01-01 .. 2025-12-31 (before any forecast of the book), pulled to 50% as (continued + 500) / (transitions + 1000); an indicator under 200 transitions stays at 50%", "sessions": 2, "since": "2026-10-20", "window_sha256": "55fea5def3d130d0c88faa011fce0df2fb7033963495cff930ff6efdc7ffe36e", "window_transitions": { "BRENT": 4558, "BTC": 4122, "COPPER": 5002, "DJI": 5026, "DXY": 4971, "GOLD": 5005, "NDX": 5028, "SOX": 5027, "SPX": 5027, "US10Y": 4943, "VIX": 5006, "WTI": 5012 } }, "n_eff": { "beyond_note": "voices left after the consensus of each indicator is taken out: 1 + the participation ratio of the correlation of the deviations; close to the number of seats when they differ each in their own way, lower when camps of seats agree beyond the common signal", "counted": { "ci_label": "clusters = runs (counted runs only)", "late_seats": [ "meta" ], "late_unit": "answers (seat x run) sealed after the reference price", "mean": { "n_eff": 1.81, "n_eff_ci": null }, "n_late_excluded": 1, "one_per_group": { "drops": [ "NDX", "DJI", "BRENT" ], "per_run": [ { "indicators": 9, "n_eff": 1.69, "n_eff_beyond_consensus": 4.21, "n_eff_participation": 2.18, "rho": 0.523, "run": "2026-10-19-am", "seats": 7, "seats_after_reference": [], "seats_counted": [ "chatgpt", "claude", "deepseek", "gemini", "grok", "kimi", "mimo" ], "time_basis": { "chatgpt": "book_sealed_at", "claude": "book_sealed_at", "deepseek": "book_sealed_at", "gemini": "book_sealed_at", "grok": "book_sealed_at", "kimi": "book_sealed_at", "mimo": "book_sealed_at" } }, { "indicators": 9, "n_eff": 1.57, "n_eff_beyond_consensus": 4.11, "n_eff_participation": 1.88, "rho": 0.586, "run": "2026-10-20-am", "seats": 8, "seats_after_reference": [ "meta" ], "seats_counted": [ "chatgpt", "claude", "deepseek", "gemini", "grok", "mimo", "stepfun", "wenxin" ], "time_basis": { "chatgpt": "book_sealed_at", "claude": "book_sealed_at", "deepseek": "book_sealed_at", "gemini": "book_sealed_at", "grok": "book_sealed_at", "meta": "book_sealed_at", "mimo": "book_sealed_at", "stepfun": "book_sealed_at", "wenxin": "book_sealed_at" } }, { "indicators": 9, "n_eff": 2.09, "n_eff_beyond_consensus": 5.43, "n_eff_participation": 2.78, "rho": 0.414, "run": "2026-10-21-am", "seats": 9, "seats_after_reference": [], "seats_counted": [ "chatgpt", "claude", "deepseek", "gemini", "grok", "meta", "mimo", "stepfun", "zai" ], "time_basis": { "chatgpt": "book_sealed_at", "claude": "book_sealed_at", "deepseek": "book_sealed_at", "gemini": "book_sealed_at", "grok": "book_sealed_at", "meta": "book_sealed_at", "mimo": "book_sealed_at", "stepfun": "book_sealed_at", "zai": "book_sealed_at" } } ] }, "per_run": [ { "indicators": 12, "n_eff": 1.74, "n_eff_beyond_consensus": 4.41, "n_eff_participation": 2.28, "rho": 0.505, "run": "2026-10-19-am", "seats": 7, "seats_after_reference": [], "seats_counted": [ "chatgpt", "claude", "deepseek", "gemini", "grok", "kimi", "mimo" ], "time_basis": { "chatgpt": "book_sealed_at", "claude": "book_sealed_at", "deepseek": "book_sealed_at", "gemini": "book_sealed_at", "grok": "book_sealed_at", "kimi": "book_sealed_at", "mimo": "book_sealed_at" } }, { "indicators": 12, "n_eff": 1.46, "n_eff_beyond_consensus": 4.48, "n_eff_participation": 1.79, "rho": 0.64, "run": "2026-10-20-am", "seats": 8, "seats_after_reference": [ "meta" ], "seats_counted": [ "chatgpt", "claude", "deepseek", "gemini", "grok", "mimo", "stepfun", "wenxin" ], "time_basis": { "chatgpt": "book_sealed_at", "claude": "book_sealed_at", "deepseek": "book_sealed_at", "gemini": "book_sealed_at", "grok": "book_sealed_at", "meta": "book_sealed_at", "mimo": "book_sealed_at", "stepfun": "book_sealed_at", "wenxin": "book_sealed_at" } }, { "indicators": 12, "n_eff": 2.23, "n_eff_beyond_consensus": 5.45, "n_eff_participation": 3.28, "rho": 0.379, "run": "2026-10-21-am", "seats": 9, "seats_after_reference": [], "seats_counted": [ "chatgpt", "claude", "deepseek", "gemini", "grok", "meta", "mimo", "stepfun", "zai" ], "time_basis": { "chatgpt": "book_sealed_at", "claude": "book_sealed_at", "deepseek": "book_sealed_at", "gemini": "book_sealed_at", "grok": "book_sealed_at", "meta": "book_sealed_at", "mimo": "book_sealed_at", "stepfun": "book_sealed_at", "zai": "book_sealed_at" } } ], "rule": "only runs whose score line counts for their session; only answers sealed strictly before the reference price (09:30 ET of the session; BTC the seal minute); a seat answering after it is out of that run", "runs": 3, "time_basis": "the book's seal time of the answer line max(at, booked_at), as the score takes it (basis `book_sealed_at`); answered_at (metas.at) only for a run with no answer line in the book; `time_basis` per run and seat" }, "label": "by the correlation of probabilities, including the link between markets; all answering seats, no cut by the seal time (main: `counted`)", "mean": { "n_eff": 2.25, "n_eff_ci": { "approximate": true, "clusters": 7, "hi": 3.0699, "level": 0.95, "lo": 1.4301, "method": "student_t_on_session_means", "resamples": 0 }, "n_eff_participation": 2.45, "rho": 0.43 }, "measures": "picture_similarity", "method": "for each run: mean pairwise correlation of the seats probabilities across the indicators (rho), n_eff = n/(1+(n-1)rho); participation ratio of the same matrix as a check; the interval is drawn by runs. per_run = ALL seats that answered, with no cut by the seal time (a late answer is in); the number for the score of the day is `counted` (only counted runs, only answers sealed before the reference price)", "n_eff_beyond_consensus": 4.14, "n_eff_errors": { "measures": "error_independence", "method": "per scored session: mean pairwise correlation of the seats' error indicators across the indicators, n_eff = n/(1+(n-1)rho); averaged over sessions", "n_eff": 2.24, "per_session": [ { "n_eff": 1.88, "rho": 0.455, "seats": 7, "session": "2026-10-19" }, { "n_eff": 2.71, "rho": 0.29, "seats": 9, "session": "2026-10-20" }, { "n_eff": 2.14, "rho": 0.401, "seats": 9, "session": "2026-10-21" } ], "rho": 0.382, "sessions": 3 }, "one_per_group": { "drops": [ "NDX", "DJI", "BRENT" ], "n_eff": 2.43, "per_run": [ { "indicators": 9, "n_eff": 4.56, "n_eff_beyond_consensus": 3.52, "n_eff_participation": 3.12, "rho": 0.122, "run": "2026-10-16-eve", "seats": 9 }, { "indicators": 9, "n_eff": 3.05, "n_eff_beyond_consensus": 3.53, "n_eff_participation": 2.08, "rho": 0.244, "run": "2026-10-17-btc", "seats": 9 }, { "indicators": 9, "n_eff": 2.39, "n_eff_beyond_consensus": 3.62, "n_eff_participation": 3.11, "rho": 0.335, "run": "2026-10-18-radar", "seats": 8 }, { "indicators": 9, "n_eff": 1.69, "n_eff_beyond_consensus": 4.21, "n_eff_participation": 2.18, "rho": 0.523, "run": "2026-10-19-am", "seats": 7 }, { "indicators": 9, "n_eff": 1.5, "n_eff_beyond_consensus": 4.07, "n_eff_participation": 1.77, "rho": 0.626, "run": "2026-10-20-am", "seats": 9 }, { "indicators": 9, "n_eff": 2.11, "n_eff_beyond_consensus": 5.61, "n_eff_participation": 2.8, "rho": 0.409, "run": "2026-10-21-am", "seats": 9 }, { "indicators": 9, "n_eff": 1.72, "n_eff_beyond_consensus": 3.41, "n_eff_participation": 2.1, "rho": 0.53, "run": "2026-10-22-am", "seats": 9 } ], "rho": 0.4 }, "per_run": [ { "indicators": 12, "n_eff": 4.01, "n_eff_beyond_consensus": 3.56, "n_eff_participation": 3.05, "rho": 0.156, "run": "2026-10-16-eve", "seats": 9 }, { "indicators": 12, "n_eff": 2.69, "n_eff_beyond_consensus": 3.72, "n_eff_participation": 2.06, "rho": 0.293, "run": "2026-10-17-btc", "seats": 9 }, { "indicators": 12, "n_eff": 2.06, "n_eff_beyond_consensus": 3.7, "n_eff_participation": 2.79, "rho": 0.411, "run": "2026-10-18-radar", "seats": 8 }, { "indicators": 12, "n_eff": 1.74, "n_eff_beyond_consensus": 4.41, "n_eff_participation": 2.28, "rho": 0.505, "run": "2026-10-19-am", "seats": 7 }, { "indicators": 12, "n_eff": 1.41, "n_eff_beyond_consensus": 4.54, "n_eff_participation": 1.69, "rho": 0.672, "run": "2026-10-20-am", "seats": 9 }, { "indicators": 12, "n_eff": 2.24, "n_eff_beyond_consensus": 5.79, "n_eff_participation": 3.3, "rho": 0.377, "run": "2026-10-21-am", "seats": 9 }, { "indicators": 12, "n_eff": 1.6, "n_eff_beyond_consensus": 3.27, "n_eff_participation": 1.98, "rho": 0.58, "run": "2026-10-22-am", "seats": 9 } ], "runs": 7, "what_it_is": "how alike the seats' probability pictures across the indicators are (the correlation of their probabilities), over all who answered, without the seal-time cut (see `counted` for the main number); NOT the independence of their errors — see n_eff_errors" }, "n_eff_by_horizon": { "horizons": { "1d": { "mean_of_runs": 1.76, "mean_vs_mean_rho_note": "mean_of_runs = the mean of the runs' N_eff; n_eff_at_mean_rho = N_eff at the mean rho (and mean seats). N_eff = n/(1+(n-1)rho) is convex in rho for rho >= 0 (the runs' rho here), so by Jensen's inequality the mean of the runs is >= N_eff at the mean rho; the gap grows with the spread of rho between runs", "n_eff": 1.76, "n_eff_at_mean_rho": 1.72, "n_eff_clim": 1.93, "n_eff_sign_free": 1.75, "n_probs": 392, "one_per_group": { "n_eff": 1.77, "rho": 0.512, "runs": 4 }, "per_run": [ { "indicators": 12, "n_eff": 1.74, "n_eff_clim": 2.85, "n_eff_sign_free": 1.85, "rho": 0.505, "rho_clim": 0.243, "rho_diff_1d_1m": 0.184, "rho_sign_free": 0.464, "run": "2026-10-19-am", "seats": 7, "spread_pp": 4.18 }, { "indicators": 12, "n_eff": 1.46, "n_eff_clim": 1.16, "n_eff_sign_free": 1.54, "rho": 0.64, "rho_clim": 0.842, "rho_diff_1d_1m": 0.356, "rho_sign_free": 0.599, "run": "2026-10-20-am", "seats": 8, "spread_pp": 3.52 }, { "indicators": 12, "n_eff": 2.23, "n_eff_clim": 2.5, "n_eff_sign_free": 1.95, "rho": 0.379, "rho_clim": 0.324, "rho_diff_1d_1m": 0.036, "rho_sign_free": 0.453, "run": "2026-10-21-am", "seats": 9, "spread_pp": 4.26 }, { "indicators": 12, "n_eff": 1.6, "n_eff_clim": 1.19, "n_eff_sign_free": 1.65, "rho": 0.576, "rho_clim": 0.823, "rho_diff_1d_1m": 0.33, "rho_sign_free": 0.557, "run": "2026-10-22-am", "seats": 9, "spread_pp": 6.11 } ], "rho": 0.525, "runs": 4, "runs_seen": 4, "seats": 8.2, "spread": { "per_run": [ { "by_market": { "BRENT": { "n": 7, "p_max": 55.0, "p_min": 34.0, "spread_pp": 6.25 }, "BTC": { "n": 7, "p_max": 56.0, "p_min": 47.0, "spread_pp": 2.76 }, "COPPER": { "n": 7, "p_max": 60.0, "p_min": 51.0, "spread_pp": 3.25 }, "DJI": { "n": 7, "p_max": 56.0, "p_min": 51.0, "spread_pp": 1.58 }, "DXY": { "n": 7, "p_max": 55.0, "p_min": 46.0, "spread_pp": 2.91 }, "GOLD": { "n": 7, "p_max": 56.0, "p_min": 52.0, "spread_pp": 1.46 }, "NDX": { "n": 7, "p_max": 62.0, "p_min": 46.0, "spread_pp": 4.85 }, "SOX": { "n": 7, "p_max": 61.0, "p_min": 38.0, "spread_pp": 8.19 }, "SPX": { "n": 7, "p_max": 62.0, "p_min": 54.0, "spread_pp": 2.76 }, "US10Y": { "n": 6, "p_max": 55.0, "p_min": 38.0, "spread_pp": 6.07 }, "VIX": { "n": 7, "p_max": 45.0, "p_min": 35.0, "spread_pp": 3.61 }, "WTI": { "n": 7, "p_max": 54.0, "p_min": 33.0, "spread_pp": 6.45 } }, "markets": 12, "run": "2026-10-19-am", "spread_pp": 4.18 }, { "by_market": { "BRENT": { "n": 8, "p_max": 68.0, "p_min": 47.0, "spread_pp": 5.76 }, "BTC": { "n": 8, "p_max": 49.0, "p_min": 43.0, "spread_pp": 1.58 }, "COPPER": { "n": 8, "p_max": 55.0, "p_min": 50.0, "spread_pp": 1.54 }, "DJI": { "n": 8, "p_max": 57.0, "p_min": 48.0, "spread_pp": 2.55 }, "DXY": { "n": 8, "p_max": 56.0, "p_min": 48.0, "spread_pp": 2.12 }, "GOLD": { "n": 8, "p_max": 55.0, "p_min": 44.0, "spread_pp": 3.08 }, "NDX": { "n": 8, "p_max": 47.0, "p_min": 38.0, "spread_pp": 2.59 }, "SOX": { "n": 8, "p_max": 48.0, "p_min": 35.0, "spread_pp": 4.42 }, "SPX": { "n": 8, "p_max": 55.0, "p_min": 44.0, "spread_pp": 3.42 }, "US10Y": { "n": 8, "p_max": 58.0, "p_min": 47.0, "spread_pp": 3.37 }, "VIX": { "n": 8, "p_max": 62.0, "p_min": 43.0, "spread_pp": 5.36 }, "WTI": { "n": 8, "p_max": 70.0, "p_min": 46.0, "spread_pp": 6.4 } }, "markets": 12, "run": "2026-10-20-am", "spread_pp": 3.52 }, { "by_market": { "BRENT": { "n": 9, "p_max": 70.0, "p_min": 51.0, "spread_pp": 5.32 }, "BTC": { "n": 8, "p_max": 60.0, "p_min": 45.0, "spread_pp": 4.2 }, "COPPER": { "n": 9, "p_max": 53.0, "p_min": 44.0, "spread_pp": 2.73 }, "DJI": { "n": 9, "p_max": 60.0, "p_min": 48.0, "spread_pp": 4.19 }, "DXY": { "n": 9, "p_max": 56.0, "p_min": 45.0, "spread_pp": 3.33 }, "GOLD": { "n": 9, "p_max": 58.0, "p_min": 47.0, "spread_pp": 3.29 }, "NDX": { "n": 9, "p_max": 68.0, "p_min": 46.0, "spread_pp": 6.53 }, "SOX": { "n": 9, "p_max": 58.0, "p_min": 44.0, "spread_pp": 3.97 }, "SPX": { "n": 9, "p_max": 62.0, "p_min": 48.0, "spread_pp": 3.63 }, "US10Y": { "n": 9, "p_max": 58.0, "p_min": 45.0, "spread_pp": 4.19 }, "VIX": { "n": 9, "p_max": 53.0, "p_min": 38.0, "spread_pp": 5.03 }, "WTI": { "n": 9, "p_max": 68.0, "p_min": 52.0, "spread_pp": 4.67 } }, "markets": 12, "run": "2026-10-21-am", "spread_pp": 4.26 }, { "by_market": { "BRENT": { "n": 9, "p_max": 73.0, "p_min": 52.0, "spread_pp": 6.71 }, "BTC": { "n": 7, "p_max": 48.0, "p_min": 35.0, "spread_pp": 3.96 }, "COPPER": { "n": 9, "p_max": 51.0, "p_min": 40.0, "spread_pp": 4.11 }, "DJI": { "n": 9, "p_max": 58.0, "p_min": 42.0, "spread_pp": 4.86 }, "DXY": { "n": 9, "p_max": 59.0, "p_min": 48.0, "spread_pp": 3.3 }, "GOLD": { "n": 9, "p_max": 52.0, "p_min": 38.0, "spread_pp": 3.71 }, "NDX": { "n": 9, "p_max": 52.0, "p_min": 28.0, "spread_pp": 8.01 }, "SOX": { "n": 9, "p_max": 50.0, "p_min": 22.0, "spread_pp": 9.09 }, "SPX": { "n": 9, "p_max": 55.0, "p_min": 32.0, "spread_pp": 6.87 }, "US10Y": { "n": 9, "p_max": 63.0, "p_min": 40.0, "spread_pp": 7.42 }, "VIX": { "n": 9, "p_max": 68.0, "p_min": 43.0, "spread_pp": 8.93 }, "WTI": { "n": 9, "p_max": 71.0, "p_min": 52.0, "spread_pp": 6.39 } }, "markets": 12, "run": "2026-10-22-am", "spread_pp": 6.11 } ], "runs": 4, "spread_pp": 4.52 } }, "1m": { "mean_of_runs": 2.63, "mean_vs_mean_rho_note": "mean_of_runs = the mean of the runs' N_eff; n_eff_at_mean_rho = N_eff at the mean rho (and mean seats). N_eff = n/(1+(n-1)rho) is convex in rho for rho >= 0 (the runs' rho here), so by Jensen's inequality the mean of the runs is >= N_eff at the mean rho; the gap grows with the spread of rho between runs", "n_eff": 2.63, "n_eff_at_mean_rho": 2.61, "n_eff_clim": 1.23, "n_eff_sign_free": 2.75, "n_probs": 388, "one_per_group": { "n_eff": 3.02, "rho": 0.251, "runs": 4 }, "per_run": [ { "indicators": 12, "n_eff": 2.39, "n_eff_clim": 1.21, "n_eff_sign_free": 2.85, "rho": 0.321, "rho_clim": 0.801, "rho_sign_free": 0.242, "run": "2026-10-19-am", "seats": 7, "spread_pp": 7.42 }, { "indicators": 12, "n_eff": 2.68, "n_eff_clim": 1.26, "n_eff_sign_free": 2.35, "rho": 0.284, "rho_clim": 0.765, "rho_sign_free": 0.343, "run": "2026-10-20-am", "seats": 8, "spread_pp": 6.21 }, { "indicators": 12, "n_eff": 2.41, "n_eff_clim": 1.19, "n_eff_sign_free": 2.28, "rho": 0.343, "rho_clim": 0.824, "rho_sign_free": 0.369, "run": "2026-10-21-am", "seats": 9, "spread_pp": 5.68 }, { "indicators": 12, "n_eff": 3.04, "n_eff_clim": 1.27, "n_eff_sign_free": 3.5, "rho": 0.246, "rho_clim": 0.76, "rho_sign_free": 0.196, "run": "2026-10-22-am", "seats": 9, "spread_pp": 7.0 } ], "rho": 0.298, "runs": 4, "runs_seen": 4, "seats": 8.2, "spread": { "per_run": [ { "by_market": { "BRENT": { "n": 7, "p_max": 66.0, "p_min": 40.0, "spread_pp": 9.89 }, "BTC": { "n": 7, "p_max": 55.0, "p_min": 38.0, "spread_pp": 7.37 }, "COPPER": { "n": 7, "p_max": 62.0, "p_min": 40.0, "spread_pp": 6.74 }, "DJI": { "n": 7, "p_max": 61.0, "p_min": 55.0, "spread_pp": 2.14 }, "DXY": { "n": 5, "p_max": 65.0, "p_min": 42.0, "spread_pp": 7.96 }, "GOLD": { "n": 7, "p_max": 58.0, "p_min": 52.0, "spread_pp": 2.17 }, "NDX": { "n": 7, "p_max": 57.0, "p_min": 32.0, "spread_pp": 8.35 }, "SOX": { "n": 7, "p_max": 56.0, "p_min": 32.0, "spread_pp": 8.04 }, "SPX": { "n": 7, "p_max": 60.0, "p_min": 35.0, "spread_pp": 9.35 }, "US10Y": { "n": 5, "p_max": 66.0, "p_min": 50.0, "spread_pp": 6.02 }, "VIX": { "n": 6, "p_max": 64.0, "p_min": 37.0, "spread_pp": 11.25 }, "WTI": { "n": 7, "p_max": 65.0, "p_min": 38.0, "spread_pp": 9.76 } }, "markets": 12, "run": "2026-10-19-am", "spread_pp": 7.42 }, { "by_market": { "BRENT": { "n": 8, "p_max": 72.0, "p_min": 43.0, "spread_pp": 9.82 }, "BTC": { "n": 8, "p_max": 55.0, "p_min": 40.0, "spread_pp": 5.0 }, "COPPER": { "n": 8, "p_max": 62.0, "p_min": 45.0, "spread_pp": 4.48 }, "DJI": { "n": 8, "p_max": 63.0, "p_min": 54.0, "spread_pp": 2.6 }, "DXY": { "n": 8, "p_max": 62.0, "p_min": 52.0, "spread_pp": 3.71 }, "GOLD": { "n": 8, "p_max": 63.0, "p_min": 35.0, "spread_pp": 8.63 }, "NDX": { "n": 8, "p_max": 56.0, "p_min": 38.0, "spread_pp": 4.92 }, "SOX": { "n": 8, "p_max": 55.0, "p_min": 38.0, "spread_pp": 6.1 }, "SPX": { "n": 8, "p_max": 58.0, "p_min": 42.0, "spread_pp": 4.99 }, "US10Y": { "n": 8, "p_max": 72.0, "p_min": 52.0, "spread_pp": 6.0 }, "VIX": { "n": 8, "p_max": 70.0, "p_min": 36.0, "spread_pp": 9.9 }, "WTI": { "n": 8, "p_max": 65.0, "p_min": 42.0, "spread_pp": 8.38 } }, "markets": 12, "run": "2026-10-20-am", "spread_pp": 6.21 }, { "by_market": { "BRENT": { "n": 9, "p_max": 62.0, "p_min": 42.0, "spread_pp": 7.71 }, "BTC": { "n": 8, "p_max": 60.0, "p_min": 42.0, "spread_pp": 5.36 }, "COPPER": { "n": 9, "p_max": 60.0, "p_min": 42.0, "spread_pp": 4.79 }, "DJI": { "n": 9, "p_max": 63.0, "p_min": 52.0, "spread_pp": 3.72 }, "DXY": { "n": 9, "p_max": 64.0, "p_min": 52.0, "spread_pp": 3.65 }, "GOLD": { "n": 9, "p_max": 62.0, "p_min": 42.0, "spread_pp": 6.13 }, "NDX": { "n": 9, "p_max": 56.0, "p_min": 38.0, "spread_pp": 5.21 }, "SOX": { "n": 9, "p_max": 55.0, "p_min": 38.0, "spread_pp": 6.76 }, "SPX": { "n": 9, "p_max": 58.0, "p_min": 42.0, "spread_pp": 5.09 }, "US10Y": { "n": 9, "p_max": 65.0, "p_min": 42.0, "spread_pp": 6.45 }, "VIX": { "n": 9, "p_max": 62.0, "p_min": 40.0, "spread_pp": 6.35 }, "WTI": { "n": 9, "p_max": 64.0, "p_min": 45.0, "spread_pp": 6.9 } }, "markets": 12, "run": "2026-10-21-am", "spread_pp": 5.68 }, { "by_market": { "BRENT": { "n": 9, "p_max": 63.0, "p_min": 44.0, "spread_pp": 5.63 }, "BTC": { "n": 7, "p_max": 55.0, "p_min": 35.0, "spread_pp": 7.67 }, "COPPER": { "n": 9, "p_max": 69.0, "p_min": 38.0, "spread_pp": 9.3 }, "DJI": { "n": 9, "p_max": 68.0, "p_min": 50.0, "spread_pp": 4.5 }, "DXY": { "n": 9, "p_max": 60.0, "p_min": 52.0, "spread_pp": 3.38 }, "GOLD": { "n": 9, "p_max": 70.0, "p_min": 38.0, "spread_pp": 9.7 }, "NDX": { "n": 9, "p_max": 54.0, "p_min": 33.0, "spread_pp": 7.67 }, "SOX": { "n": 9, "p_max": 55.0, "p_min": 30.0, "spread_pp": 9.19 }, "SPX": { "n": 9, "p_max": 58.0, "p_min": 38.0, "spread_pp": 6.95 }, "US10Y": { "n": 9, "p_max": 62.0, "p_min": 48.0, "spread_pp": 4.45 }, "VIX": { "n": 9, "p_max": 60.0, "p_min": 32.0, "spread_pp": 9.4 }, "WTI": { "n": 9, "p_max": 63.0, "p_min": 45.0, "spread_pp": 6.2 } }, "markets": 12, "run": "2026-10-22-am", "spread_pp": 7.0 } ], "runs": 4, "spread_pp": 6.58 } }, "1w": { "mean_of_runs": 2.19, "mean_vs_mean_rho_note": "mean_of_runs = the mean of the runs' N_eff; n_eff_at_mean_rho = N_eff at the mean rho (and mean seats). N_eff = n/(1+(n-1)rho) is convex in rho for rho >= 0 (the runs' rho here), so by Jensen's inequality the mean of the runs is >= N_eff at the mean rho; the gap grows with the spread of rho between runs", "n_eff": 2.19, "n_eff_at_mean_rho": 2.02, "n_eff_clim": 1.42, "n_eff_sign_free": 1.99, "n_probs": 389, "one_per_group": { "n_eff": 2.57, "rho": 0.36, "runs": 4 }, "per_run": [ { "indicators": 12, "n_eff": 2.81, "n_eff_clim": 1.96, "n_eff_sign_free": 2.67, "rho": 0.248, "rho_clim": 0.429, "rho_sign_free": 0.271, "run": "2026-10-19-am", "seats": 7, "spread_pp": 6.33 }, { "indicators": 12, "n_eff": 1.99, "n_eff_clim": 1.16, "n_eff_sign_free": 1.96, "rho": 0.432, "rho_clim": 0.84, "rho_sign_free": 0.439, "run": "2026-10-20-am", "seats": 8, "spread_pp": 5.74 }, { "indicators": 12, "n_eff": 2.63, "n_eff_clim": 1.39, "n_eff_sign_free": 1.95, "rho": 0.302, "rho_clim": 0.684, "rho_sign_free": 0.453, "run": "2026-10-21-am", "seats": 9, "spread_pp": 4.77 }, { "indicators": 12, "n_eff": 1.34, "n_eff_clim": 1.17, "n_eff_sign_free": 1.38, "rho": 0.713, "rho_clim": 0.834, "rho_sign_free": 0.687, "run": "2026-10-22-am", "seats": 9, "spread_pp": 5.26 } ], "rho": 0.424, "runs": 4, "runs_seen": 4, "seats": 8.2, "spread": { "per_run": [ { "by_market": { "BRENT": { "n": 7, "p_max": 64.0, "p_min": 44.0, "spread_pp": 6.82 }, "BTC": { "n": 7, "p_max": 60.0, "p_min": 43.0, "spread_pp": 5.83 }, "COPPER": { "n": 7, "p_max": 62.0, "p_min": 45.0, "spread_pp": 5.09 }, "DJI": { "n": 7, "p_max": 64.0, "p_min": 55.0, "spread_pp": 3.45 }, "DXY": { "n": 6, "p_max": 62.0, "p_min": 50.0, "spread_pp": 3.68 }, "GOLD": { "n": 7, "p_max": 62.0, "p_min": 47.0, "spread_pp": 4.39 }, "NDX": { "n": 7, "p_max": 57.0, "p_min": 40.0, "spread_pp": 6.74 }, "SOX": { "n": 7, "p_max": 57.0, "p_min": 35.0, "spread_pp": 7.14 }, "SPX": { "n": 7, "p_max": 62.0, "p_min": 42.0, "spread_pp": 6.54 }, "US10Y": { "n": 6, "p_max": 62.0, "p_min": 42.0, "spread_pp": 6.8 }, "VIX": { "n": 5, "p_max": 63.0, "p_min": 32.0, "spread_pp": 13.27 }, "WTI": { "n": 7, "p_max": 63.0, "p_min": 44.0, "spread_pp": 6.18 } }, "markets": 12, "run": "2026-10-19-am", "spread_pp": 6.33 }, { "by_market": { "BRENT": { "n": 8, "p_max": 75.0, "p_min": 46.0, "spread_pp": 7.89 }, "BTC": { "n": 8, "p_max": 52.0, "p_min": 38.0, "spread_pp": 4.89 }, "COPPER": { "n": 8, "p_max": 58.0, "p_min": 42.0, "spread_pp": 4.33 }, "DJI": { "n": 8, "p_max": 60.0, "p_min": 52.0, "spread_pp": 2.45 }, "DXY": { "n": 8, "p_max": 59.0, "p_min": 51.0, "spread_pp": 2.83 }, "GOLD": { "n": 8, "p_max": 59.0, "p_min": 40.0, "spread_pp": 6.58 }, "NDX": { "n": 8, "p_max": 54.0, "p_min": 30.0, "spread_pp": 6.46 }, "SOX": { "n": 8, "p_max": 54.0, "p_min": 28.0, "spread_pp": 6.81 }, "SPX": { "n": 8, "p_max": 55.0, "p_min": 40.0, "spread_pp": 5.69 }, "US10Y": { "n": 8, "p_max": 61.0, "p_min": 50.0, "spread_pp": 3.28 }, "VIX": { "n": 8, "p_max": 75.0, "p_min": 44.0, "spread_pp": 8.75 }, "WTI": { "n": 8, "p_max": 78.0, "p_min": 45.0, "spread_pp": 8.89 } }, "markets": 12, "run": "2026-10-20-am", "spread_pp": 5.74 }, { "by_market": { "BRENT": { "n": 9, "p_max": 66.0, "p_min": 50.0, "spread_pp": 4.69 }, "BTC": { "n": 8, "p_max": 58.0, "p_min": 43.0, "spread_pp": 5.21 }, "COPPER": { "n": 9, "p_max": 57.0, "p_min": 42.0, "spread_pp": 5.47 }, "DJI": { "n": 9, "p_max": 65.0, "p_min": 54.0, "spread_pp": 3.16 }, "DXY": { "n": 9, "p_max": 60.0, "p_min": 48.0, "spread_pp": 3.5 }, "GOLD": { "n": 9, "p_max": 61.0, "p_min": 45.0, "spread_pp": 4.71 }, "NDX": { "n": 9, "p_max": 55.0, "p_min": 40.0, "spread_pp": 4.81 }, "SOX": { "n": 9, "p_max": 59.0, "p_min": 36.0, "spread_pp": 6.72 }, "SPX": { "n": 9, "p_max": 59.0, "p_min": 47.0, "spread_pp": 4.13 }, "US10Y": { "n": 9, "p_max": 62.0, "p_min": 44.0, "spread_pp": 5.31 }, "VIX": { "n": 9, "p_max": 62.0, "p_min": 44.0, "spread_pp": 5.72 }, "WTI": { "n": 9, "p_max": 64.0, "p_min": 50.0, "spread_pp": 3.87 } }, "markets": 12, "run": "2026-10-21-am", "spread_pp": 4.77 }, { "by_market": { "BRENT": { "n": 9, "p_max": 70.0, "p_min": 53.0, "spread_pp": 4.61 }, "BTC": { "n": 7, "p_max": 52.0, "p_min": 40.0, "spread_pp": 4.95 }, "COPPER": { "n": 9, "p_max": 60.0, "p_min": 38.0, "spread_pp": 6.17 }, "DJI": { "n": 9, "p_max": 64.0, "p_min": 52.0, "spread_pp": 3.6 }, "DXY": { "n": 9, "p_max": 64.0, "p_min": 50.0, "spread_pp": 3.98 }, "GOLD": { "n": 9, "p_max": 65.0, "p_min": 42.0, "spread_pp": 7.18 }, "NDX": { "n": 9, "p_max": 51.0, "p_min": 32.0, "spread_pp": 5.85 }, "SOX": { "n": 9, "p_max": 49.0, "p_min": 28.0, "spread_pp": 5.98 }, "SPX": { "n": 9, "p_max": 55.0, "p_min": 40.0, "spread_pp": 5.4 }, "US10Y": { "n": 9, "p_max": 65.0, "p_min": 50.0, "spread_pp": 4.57 }, "VIX": { "n": 9, "p_max": 62.0, "p_min": 42.0, "spread_pp": 6.16 }, "WTI": { "n": 9, "p_max": 69.0, "p_min": 52.0, "spread_pp": 4.65 } }, "markets": 12, "run": "2026-10-22-am", "spread_pp": 5.26 } ], "runs": 4, "spread_pp": 5.53 } }, "6m": { "mean_of_runs": 1.28, "mean_vs_mean_rho_note": "mean_of_runs = the mean of the runs' N_eff; n_eff_at_mean_rho = N_eff at the mean rho (and mean seats). N_eff = n/(1+(n-1)rho) is convex in rho for rho >= 0 (the runs' rho here), so by Jensen's inequality the mean of the runs is >= N_eff at the mean rho; the gap grows with the spread of rho between runs", "n_eff": 1.28, "n_eff_at_mean_rho": 1.26, "n_eff_clim": 1.15, "n_eff_sign_free": 1.31, "n_probs": 392, "one_per_group": { "n_eff": 1.29, "rho": 0.763, "runs": 4 }, "per_run": [ { "indicators": 12, "n_eff": 1.16, "n_eff_clim": 1.13, "n_eff_sign_free": 1.17, "rho": 0.838, "rho_clim": 0.863, "rho_sign_free": 0.834, "run": "2026-10-19-am", "seats": 7, "spread_pp": 5.09 }, { "indicators": 12, "n_eff": 1.14, "n_eff_clim": 1.11, "n_eff_sign_free": 1.16, "rho": 0.859, "rho_clim": 0.888, "rho_sign_free": 0.846, "run": "2026-10-20-am", "seats": 8, "spread_pp": 4.69 }, { "indicators": 12, "n_eff": 1.58, "n_eff_clim": 1.18, "n_eff_sign_free": 1.56, "rho": 0.589, "rho_clim": 0.826, "rho_sign_free": 0.596, "run": "2026-10-21-am", "seats": 9, "spread_pp": 6.77 }, { "indicators": 12, "n_eff": 1.25, "n_eff_clim": 1.16, "n_eff_sign_free": 1.35, "rho": 0.776, "rho_clim": 0.848, "rho_sign_free": 0.708, "run": "2026-10-22-am", "seats": 9, "spread_pp": 5.57 } ], "rho": 0.765, "runs": 4, "runs_seen": 4, "seats": 8.2, "spread": { "per_run": [ { "by_market": { "BRENT": { "n": 7, "p_max": 58.0, "p_min": 30.0, "spread_pp": 8.62 }, "BTC": { "n": 7, "p_max": 68.0, "p_min": 58.0, "spread_pp": 3.55 }, "COPPER": { "n": 7, "p_max": 73.0, "p_min": 55.0, "spread_pp": 6.11 }, "DJI": { "n": 7, "p_max": 72.0, "p_min": 58.0, "spread_pp": 3.88 }, "DXY": { "n": 7, "p_max": 45.0, "p_min": 35.0, "spread_pp": 3.09 }, "GOLD": { "n": 7, "p_max": 74.0, "p_min": 60.0, "spread_pp": 5.03 }, "NDX": { "n": 7, "p_max": 65.0, "p_min": 55.0, "spread_pp": 3.33 }, "SOX": { "n": 7, "p_max": 70.0, "p_min": 48.0, "spread_pp": 6.51 }, "SPX": { "n": 7, "p_max": 68.0, "p_min": 58.0, "spread_pp": 3.34 }, "US10Y": { "n": 6, "p_max": 40.0, "p_min": 34.0, "spread_pp": 2.69 }, "VIX": { "n": 7, "p_max": 48.0, "p_min": 28.0, "spread_pp": 6.54 }, "WTI": { "n": 7, "p_max": 57.0, "p_min": 28.0, "spread_pp": 8.42 } }, "markets": 12, "run": "2026-10-19-am", "spread_pp": 5.09 }, { "by_market": { "BRENT": { "n": 8, "p_max": 48.0, "p_min": 32.0, "spread_pp": 5.87 }, "BTC": { "n": 8, "p_max": 71.0, "p_min": 55.0, "spread_pp": 4.41 }, "COPPER": { "n": 8, "p_max": 68.0, "p_min": 53.0, "spread_pp": 4.87 }, "DJI": { "n": 8, "p_max": 68.0, "p_min": 58.0, "spread_pp": 3.2 }, "DXY": { "n": 8, "p_max": 55.0, "p_min": 40.0, "spread_pp": 5.16 }, "GOLD": { "n": 8, "p_max": 70.0, "p_min": 52.0, "spread_pp": 4.66 }, "NDX": { "n": 8, "p_max": 72.0, "p_min": 55.0, "spread_pp": 4.87 }, "SOX": { "n": 8, "p_max": 70.0, "p_min": 53.0, "spread_pp": 5.38 }, "SPX": { "n": 8, "p_max": 68.0, "p_min": 55.0, "spread_pp": 3.57 }, "US10Y": { "n": 8, "p_max": 56.0, "p_min": 35.0, "spread_pp": 6.36 }, "VIX": { "n": 8, "p_max": 40.0, "p_min": 33.0, "spread_pp": 2.38 }, "WTI": { "n": 8, "p_max": 46.0, "p_min": 32.0, "spread_pp": 5.59 } }, "markets": 12, "run": "2026-10-20-am", "spread_pp": 4.69 }, { "by_market": { "BRENT": { "n": 9, "p_max": 55.0, "p_min": 22.0, "spread_pp": 9.5 }, "BTC": { "n": 8, "p_max": 72.0, "p_min": 55.0, "spread_pp": 5.61 }, "COPPER": { "n": 9, "p_max": 70.0, "p_min": 55.0, "spread_pp": 4.97 }, "DJI": { "n": 9, "p_max": 68.0, "p_min": 55.0, "spread_pp": 3.78 }, "DXY": { "n": 9, "p_max": 56.0, "p_min": 35.0, "spread_pp": 6.45 }, "GOLD": { "n": 9, "p_max": 72.0, "p_min": 50.0, "spread_pp": 6.29 }, "NDX": { "n": 9, "p_max": 65.0, "p_min": 40.0, "spread_pp": 7.18 }, "SOX": { "n": 9, "p_max": 70.0, "p_min": 52.0, "spread_pp": 5.29 }, "SPX": { "n": 9, "p_max": 72.0, "p_min": 42.0, "spread_pp": 7.69 }, "US10Y": { "n": 9, "p_max": 60.0, "p_min": 35.0, "spread_pp": 7.58 }, "VIX": { "n": 9, "p_max": 55.0, "p_min": 30.0, "spread_pp": 8.45 }, "WTI": { "n": 9, "p_max": 54.0, "p_min": 25.0, "spread_pp": 8.41 } }, "markets": 12, "run": "2026-10-21-am", "spread_pp": 6.77 }, { "by_market": { "BRENT": { "n": 9, "p_max": 59.0, "p_min": 28.0, "spread_pp": 9.07 }, "BTC": { "n": 7, "p_max": 62.0, "p_min": 50.0, "spread_pp": 4.09 }, "COPPER": { "n": 9, "p_max": 75.0, "p_min": 55.0, "spread_pp": 5.83 }, "DJI": { "n": 9, "p_max": 72.0, "p_min": 52.0, "spread_pp": 5.28 }, "DXY": { "n": 9, "p_max": 55.0, "p_min": 40.0, "spread_pp": 4.78 }, "GOLD": { "n": 9, "p_max": 76.0, "p_min": 55.0, "spread_pp": 5.28 }, "NDX": { "n": 9, "p_max": 65.0, "p_min": 52.0, "spread_pp": 3.51 }, "SOX": { "n": 9, "p_max": 62.0, "p_min": 53.0, "spread_pp": 2.81 }, "SPX": { "n": 9, "p_max": 68.0, "p_min": 55.0, "spread_pp": 3.72 }, "US10Y": { "n": 9, "p_max": 52.0, "p_min": 34.0, "spread_pp": 5.52 }, "VIX": { "n": 9, "p_max": 55.0, "p_min": 30.0, "spread_pp": 8.2 }, "WTI": { "n": 9, "p_max": 60.0, "p_min": 29.0, "spread_pp": 8.74 } }, "markets": 12, "run": "2026-10-22-am", "spread_pp": 5.57 } ], "runs": 4, "spread_pp": 5.53 } } }, "n_eff_sign_free": "№614: Kish n_eff on the uncentred correlation of the deviations from 50 (flipping a market changes nothing), per run and horizon; n_eff_clim: the same on probability minus the climatology q_clim (markets without a climatology left out)", "rho_diff_1d_1m": { "mean": 0.227, "per_run": [ { "rho_1d": 0.505, "rho_1m": 0.321, "rho_diff_1d_1m": 0.184, "run": "2026-10-19-am" }, { "rho_1d": 0.64, "rho_1m": 0.284, "rho_diff_1d_1m": 0.356, "run": "2026-10-20-am" }, { "rho_1d": 0.379, "rho_1m": 0.343, "rho_diff_1d_1m": 0.036, "run": "2026-10-21-am" }, { "rho_1d": 0.576, "rho_1m": 0.246, "rho_diff_1d_1m": 0.33, "run": "2026-10-22-am" } ], "runs": 4, "why": "rho of the day minus rho of the month in the same run (F9 of the article: N_eff is convex in rho, noise in rho lifts the month, so the difference of rho is the input)" }, "spread": "№567: spread_pp = the population standard deviation of the seats' probabilities (percentage points) per market x horizon x run, with their min and max; per run the mean over its markets; the horizon's number = the mean over its runs. The same timely answers as n_eff", "timely": "a probability (elicited or a stated 50) from a line sealed no later than the event's reference price, the issue's one event; the last such line of a cell; session runs only", "what": "the effective voices (an estimate from the correlation of the errors; Kish n/(1+(n-1)rho), rho = the mean pairwise correlation of the models' probabilities across the indicators of a run) among the timely answers of each horizon; the number of a horizon = the mean over its runs; one_per_group = the same with NDX, DJI, BRENT left out (they repeat SPX and WTI)" }, "n_scored_sessions": 3, "pairs": { "file": "api/v1/council-pairs.csv", "interval_from_sessions": 5, "interval_rule": { "from": "2026-10-21", "rule": "The interval is of the published mean_diff itself (the mean over all common cells, a session with more cells weighs more): from 20 sessions the percentile bootstrap by sessions; from 5 to 19 a Student t on the cluster-robust (by session) standard error of that weighted mean (approximate). Before this date the 5-19 interval was a t on the unweighted session means, a different number from mean_diff; the whole file is rebuilt each time, so every pair now carries the new interval. From the same date an own-reference answer (late_ref) leaves the pairs only in sessions from 2026-10-21; earlier sessions keep it, as published." }, "late_seats": [ "meta" ], "level": 0.95, "metric": "brier_all_rows", "n_late_excluded": 1, "pairs": { "chatgpt|claude": { "a": "chatgpt", "b": "claude", "better": null, "cells": 34, "ci": null, "distinguishable": null, "mean_diff": 0.0047, "sessions": 3 }, "chatgpt|deepseek": { "a": "chatgpt", "b": "deepseek", "better": null, "cells": 33, "ci": null, "distinguishable": null, "mean_diff": 0.0159, "sessions": 3 }, "chatgpt|gemini": { "a": "chatgpt", "b": "gemini", "better": null, "cells": 35, "ci": null, "distinguishable": null, "mean_diff": -0.0013, "sessions": 3 }, "chatgpt|grok": { "a": "chatgpt", "b": "grok", "better": null, "cells": 32, "ci": null, "distinguishable": null, "mean_diff": 0.0222, "sessions": 3 }, "chatgpt|kimi": { "a": "chatgpt", "b": "kimi", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0118, "sessions": 1 }, "chatgpt|meta": { "a": "chatgpt", "b": "meta", "better": null, "cells": 19, "ci": null, "distinguishable": null, "mean_diff": 0.0431, "sessions": 2 }, "chatgpt|mimo": { "a": "chatgpt", "b": "mimo", "better": null, "cells": 33, "ci": null, "distinguishable": null, "mean_diff": -0.0231, "sessions": 3 }, "chatgpt|stepfun": { "a": "chatgpt", "b": "stepfun", "better": null, "cells": 23, "ci": null, "distinguishable": null, "mean_diff": 0.0014, "sessions": 2 }, "chatgpt|wenxin": { "a": "chatgpt", "b": "wenxin", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0512, "sessions": 1 }, "chatgpt|zai": { "a": "chatgpt", "b": "zai", "better": null, "cells": 12, "ci": null, "distinguishable": null, "mean_diff": 0.009, "sessions": 1 }, "claude|deepseek": { "a": "claude", "b": "deepseek", "better": null, "cells": 33, "ci": null, "distinguishable": null, "mean_diff": 0.0111, "sessions": 3 }, "claude|gemini": { "a": "claude", "b": "gemini", "better": null, "cells": 34, "ci": null, "distinguishable": null, "mean_diff": -0.0083, "sessions": 3 }, "claude|grok": { "a": "claude", "b": "grok", "better": null, "cells": 32, "ci": null, "distinguishable": null, "mean_diff": 0.0182, "sessions": 3 }, "claude|kimi": { "a": "claude", "b": "kimi", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0152, "sessions": 1 }, "claude|meta": { "a": "claude", "b": "meta", "better": null, "cells": 18, "ci": null, "distinguishable": null, "mean_diff": 0.0363, "sessions": 2 }, "claude|mimo": { "a": "claude", "b": "mimo", "better": null, "cells": 33, "ci": null, "distinguishable": null, "mean_diff": -0.0273, "sessions": 3 }, "claude|stepfun": { "a": "claude", "b": "stepfun", "better": null, "cells": 22, "ci": null, "distinguishable": null, "mean_diff": -0.0036, "sessions": 2 }, "claude|wenxin": { "a": "claude", "b": "wenxin", "better": null, "cells": 10, "ci": null, "distinguishable": null, "mean_diff": -0.0732, "sessions": 1 }, "claude|zai": { "a": "claude", "b": "zai", "better": null, "cells": 12, "ci": null, "distinguishable": null, "mean_diff": 0.0112, "sessions": 1 }, "deepseek|gemini": { "a": "deepseek", "b": "gemini", "better": null, "cells": 33, "ci": null, "distinguishable": null, "mean_diff": -0.022, "sessions": 3 }, "deepseek|grok": { "a": "deepseek", "b": "grok", "better": null, "cells": 31, "ci": null, "distinguishable": null, "mean_diff": 0.0057, "sessions": 3 }, "deepseek|kimi": { "a": "deepseek", "b": "kimi", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0507, "sessions": 1 }, "deepseek|meta": { "a": "deepseek", "b": "meta", "better": null, "cells": 17, "ci": null, "distinguishable": null, "mean_diff": 0.0378, "sessions": 2 }, "deepseek|mimo": { "a": "deepseek", "b": "mimo", "better": null, "cells": 32, "ci": null, "distinguishable": null, "mean_diff": -0.0368, "sessions": 3 }, "deepseek|stepfun": { "a": "deepseek", "b": "stepfun", "better": null, "cells": 21, "ci": null, "distinguishable": null, "mean_diff": -0.001, "sessions": 2 }, "deepseek|wenxin": { "a": "deepseek", "b": "wenxin", "better": null, "cells": 9, "ci": null, "distinguishable": null, "mean_diff": -0.045, "sessions": 1 }, "deepseek|zai": { "a": "deepseek", "b": "zai", "better": null, "cells": 12, "ci": null, "distinguishable": null, "mean_diff": -0.0148, "sessions": 1 }, "gemini|grok": { "a": "gemini", "b": "grok", "better": null, "cells": 32, "ci": null, "distinguishable": null, "mean_diff": 0.0255, "sessions": 3 }, "gemini|kimi": { "a": "gemini", "b": "kimi", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0156, "sessions": 1 }, "gemini|meta": { "a": "gemini", "b": "meta", "better": null, "cells": 19, "ci": null, "distinguishable": null, "mean_diff": 0.0393, "sessions": 2 }, "gemini|mimo": { "a": "gemini", "b": "mimo", "better": null, "cells": 33, "ci": null, "distinguishable": null, "mean_diff": -0.0164, "sessions": 3 }, "gemini|stepfun": { "a": "gemini", "b": "stepfun", "better": null, "cells": 23, "ci": null, "distinguishable": null, "mean_diff": 0.0069, "sessions": 2 }, "gemini|wenxin": { "a": "gemini", "b": "wenxin", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0326, "sessions": 1 }, "gemini|zai": { "a": "gemini", "b": "zai", "better": null, "cells": 12, "ci": null, "distinguishable": null, "mean_diff": 0.0024, "sessions": 1 }, "grok|kimi": { "a": "grok", "b": "kimi", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.035, "sessions": 1 }, "grok|meta": { "a": "grok", "b": "meta", "better": null, "cells": 17, "ci": null, "distinguishable": null, "mean_diff": 0.0181, "sessions": 2 }, "grok|mimo": { "a": "grok", "b": "mimo", "better": null, "cells": 31, "ci": null, "distinguishable": null, "mean_diff": -0.0449, "sessions": 3 }, "grok|stepfun": { "a": "grok", "b": "stepfun", "better": null, "cells": 21, "ci": null, "distinguishable": null, "mean_diff": -0.0192, "sessions": 2 }, "grok|wenxin": { "a": "grok", "b": "wenxin", "better": null, "cells": 9, "ci": null, "distinguishable": null, "mean_diff": -0.0612, "sessions": 1 }, "grok|zai": { "a": "grok", "b": "zai", "better": null, "cells": 12, "ci": null, "distinguishable": null, "mean_diff": -0.0309, "sessions": 1 }, "kimi|mimo": { "a": "kimi", "b": "mimo", "better": null, "cells": 10, "ci": null, "distinguishable": null, "mean_diff": -0.0563, "sessions": 1 }, "meta|mimo": { "a": "meta", "b": "mimo", "better": null, "cells": 18, "ci": null, "distinguishable": null, "mean_diff": -0.0482, "sessions": 2 }, "meta|stepfun": { "a": "meta", "b": "stepfun", "better": null, "cells": 19, "ci": null, "distinguishable": null, "mean_diff": -0.0362, "sessions": 2 }, "meta|wenxin": { "a": "meta", "b": "wenxin", "better": null, "cells": 8, "ci": null, "distinguishable": null, "mean_diff": -0.0899, "sessions": 1 }, "meta|zai": { "a": "meta", "b": "zai", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0357, "sessions": 1 }, "mimo|stepfun": { "a": "mimo", "b": "stepfun", "better": null, "cells": 22, "ci": null, "distinguishable": null, "mean_diff": 0.0089, "sessions": 2 }, "mimo|wenxin": { "a": "mimo", "b": "wenxin", "better": null, "cells": 10, "ci": null, "distinguishable": null, "mean_diff": -0.0389, "sessions": 1 }, "mimo|zai": { "a": "mimo", "b": "zai", "better": null, "cells": 12, "ci": null, "distinguishable": null, "mean_diff": 0.0056, "sessions": 1 }, "stepfun|wenxin": { "a": "stepfun", "b": "wenxin", "better": null, "cells": 11, "ci": null, "distinguishable": null, "mean_diff": -0.0421, "sessions": 1 }, "stepfun|zai": { "a": "stepfun", "b": "zai", "better": null, "cells": 12, "ci": null, "distinguishable": null, "mean_diff": -0.002, "sessions": 1 } }, "resamples": 2000, "unit": "session", "what": "Brier(a) - Brier(b) on the cells both answered on the same event (no own-reference answers); below 0: a is better" }, "portfolio_decomposition": { "accounts": { "_cash": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 0.0, "first_trades": null, "gross_usd": 22.64, "net_usd": 22.64, "sessions": 3, "shadow_net_usd": 22.64, "shadow_value": 100022.64, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 0.0, "trades_without_close": 0, "turnover": 0.0, "turnover_mean_equity": 0.0, "value": 100022.64 }, "_council": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 356.56, "fee": 60.25, "n": 5, "usd": 60213.7 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 60.25, "first_trades": "2026-10-19", "gross_usd": 425.8, "net_usd": 365.55, "sessions": 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"trade_effect_usd": 0.0, "traded_usd": 79936.0, "trades_without_close": 0, "turnover": 0.7994, "turnover_mean_equity": 0.7991, "value": 100405.61 }, "deepseek": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 452.41, "fee": 90.0, "n": 7, "usd": 89919.0 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 90.0, "first_trades": "2026-10-19", "gross_usd": 544.67, "net_usd": 454.67, "sessions": 3, "shadow_net_usd": 454.67, "shadow_value": 100454.67, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 89919.0, "trades_without_close": 0, "turnover": 0.8992, "turnover_mean_equity": 0.8979, "value": 100454.67 }, "gemini": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 420.68, "fee": 80.0, "n": 6, "usd": 79936.0 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 80.0, "first_trades": "2026-10-19", "gross_usd": 505.2, "net_usd": 425.2, "sessions": 3, "shadow_net_usd": 425.2, "shadow_value": 100425.2, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 79936.0, "trades_without_close": 0, "turnover": 0.7994, "turnover_mean_equity": 0.7977, "value": 100425.2 }, "grok": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 421.9, "fee": 70.0, "n": 5, "usd": 69951.0 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 70.0, "first_trades": "2026-10-19", "gross_usd": 498.68, "net_usd": 428.68, "sessions": 3, "shadow_net_usd": 428.68, "shadow_value": 100428.68, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 69951.0, "trades_without_close": 0, "turnover": 0.6995, "turnover_mean_equity": 0.6991, "value": 100428.68 }, "kimi": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 292.48, "fee": 90.0, "n": 6, "usd": 89929.2 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 90.01, "first_trades": "2026-10-20", "gross_usd": 394.95, "net_usd": 304.94, "sessions": 3, "shadow_net_usd": 304.94, "shadow_value": 100304.94, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 89929.2, "trades_without_close": 0, "turnover": 0.8993, "turnover_mean_equity": 0.8982, "value": 100304.94 }, "meta": { "by_kind": { "chosen": { "effect": -286.19, "fee": 60.68, "n": 7, "usd": 60667.41 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 403.87, "fee": 85.0, "n": 7, "usd": 84927.75 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 145.68, "first_trades": "2026-10-19", "gross_usd": 267.9, "net_usd": 122.22, "sessions": 3, "shadow_net_usd": 408.41, "shadow_value": 100408.41, "start": "2026-10-19", "trade_effect_usd": -286.19, "traded_usd": 145595.16, "trades_without_close": 0, "turnover": 1.456, "turnover_mean_equity": 1.4541, "value": 100122.22 }, "mimo": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 417.59, "fee": 80.0, "n": 7, "usd": 79936.0 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 80.0, "first_trades": "2026-10-19", "gross_usd": 502.12, "net_usd": 422.12, "sessions": 3, "shadow_net_usd": 422.12, "shadow_value": 100422.12, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 79936.0, "trades_without_close": 0, "turnover": 0.7994, "turnover_mean_equity": 0.8, "value": 100422.12 }, "nemotron": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 662.14, "fee": 85.0, "n": 10, "usd": 84937.39 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 85.01, "first_trades": "2026-10-20", "gross_usd": 760.18, "net_usd": 675.17, "sessions": 3, "shadow_net_usd": 675.17, "shadow_value": 100675.17, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 84937.39, "trades_without_close": 0, "turnover": 0.8494, "turnover_mean_equity": 0.8469, "value": 100675.17 }, "nova": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 175.17, "fee": 60.0, "n": 5, "usd": 59970.79 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 60.01, "first_trades": "2026-10-20", "gross_usd": 251.03, "net_usd": 191.02, "sessions": 3, "shadow_net_usd": 191.02, "shadow_value": 100191.02, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 59970.79, "trades_without_close": 0, "turnover": 0.5997, "turnover_mean_equity": 0.5994, "value": 100191.02 }, "qwen": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 1069.1, "fee": 85.0, "n": 6, "usd": 84937.38 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 85.01, "first_trades": "2026-10-20", "gross_usd": 1167.14, "net_usd": 1082.13, "sessions": 3, "shadow_net_usd": 1082.13, "shadow_value": 101082.13, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 84937.38, "trades_without_close": 0, "turnover": 0.8494, "turnover_mean_equity": 0.8454, "value": 101082.13 }, "stepfun": { "by_kind": { "chosen": { "effect": -177.87, "fee": 10.05, "n": 8, "usd": 10045.28 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 426.97, "fee": 85.0, "n": 8, "usd": 84927.75 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 95.04, "first_trades": "2026-10-19", "gross_usd": 348.65, "net_usd": 253.61, "sessions": 3, "shadow_net_usd": 431.48, "shadow_value": 100431.48, "start": "2026-10-19", "trade_effect_usd": -177.87, "traded_usd": 94973.03, "trades_without_close": 0, "turnover": 0.9497, "turnover_mean_equity": 0.9506, "value": 100253.61 }, "wenxin": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": -240.67, "fee": 80.0, "n": 5, "usd": 79945.08 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 80.01, "first_trades": "2026-10-20", "gross_usd": -147.06, "net_usd": -227.07, "sessions": 3, "shadow_net_usd": -227.07, "shadow_value": 99772.93, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 79945.08, "trades_without_close": 0, "turnover": 0.7995, "turnover_mean_equity": 0.8007, "value": 99772.93 }, "zai": { "by_kind": { "chosen": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "forced": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 }, "initial": { "effect": 245.04, "fee": 61.0, "n": 7, "usd": 60969.72 }, "rule": { "effect": 0.0, "fee": 0.0, "n": 0, "usd": 0.0 } }, "fees_usd": 61.01, "first_trades": "2026-10-20", "gross_usd": 321.79, "net_usd": 260.78, "sessions": 3, "shadow_net_usd": 260.78, "shadow_value": 100260.78, "start": "2026-10-19", "trade_effect_usd": 0.0, "traded_usd": 60969.72, "trades_without_close": 0, "turnover": 0.6097, "turnover_mean_equity": 0.609, "value": 100260.78 } }, "fields": { "accounts": "per account (a seat name, or a rule-based account with `_` or a variant tag in its name): the numbers below; an account with no value history is absent", "accounts.by_kind": "the trades by kind: initial (the first placement), chosen (a session the model decided), forced (a trade on a session it did not decide), rule (a rule-based account's later trades)", "accounts.by_kind.effect": "what the trades of the kind changed in the value to the latest close known, after their fees (side * units * (close - execution price) - fee), usd", "accounts.by_kind.fee": "the fees of the kind, usd", "accounts.by_kind.n": "the number of trades of the kind", "accounts.by_kind.usd": "the traded usd of the kind", "accounts.fees_usd": "the fees paid, usd", "accounts.first_trades": "the first session WITH trades (the first placement), not the start date; null when the account never traded", "accounts.gross_usd": "gross result = net result + fees, usd", "accounts.net_usd": "net result = last value - start capital, usd (after fees)", "accounts.sessions": "the number of sessions in the account's value history", "accounts.shadow_net_usd": "net result of the shadow = net_usd - trade_effect_usd", "accounts.shadow_value": "the shadow = the book without the trades after the first placement: last value - trade_effect_usd", "accounts.start": "the date of the account's first value in its history", "accounts.trade_effect_usd": "the effect of all the trades after the first placement (every kind but initial), usd", "accounts.traded_usd": "the sum of the traded usd, buys and sells together, over all trades", "accounts.trades_without_close": "trades with no close known for their instrument (left out of the effect)", "accounts.turnover": "turnover = traded usd / start capital", "accounts.turnover_mean_equity": "traded usd / the mean of the account's values over its history (the other measure of turnover: against the capital it really had); null when the history has no value", "accounts.value": "the last value of the account, usd", "fields": "this dictionary: key -> definition, for the keys of `accounts[*]`, `accounts[*].by_kind[*]` and `total`", "kinds": "the kinds of a trade in the order of `by_kind`: initial, chosen, forced, rule (their definitions end the text of `rule`)", "rule": "the definitions in one text: net, gross, turnover, the shadow, the kinds", "total": "over the accounts of this block", "total.accounts": "the number of accounts", "total.accounts_better_than_shadow": "the accounts whose trades after the first placement added value (trade_effect_usd above 0)", "total.accounts_worse_than_shadow": "the accounts whose trades after the first placement lost value (trade_effect_usd below 0)", "total.fees_usd": "the fees of all the accounts, usd", "total.trade_effect_usd": "the trade effect of all the accounts, usd" }, "kinds": [ "initial", "chosen", "forced", "rule" ], "rule": "net = last value - start capital; gross = net + fees; turnover = traded usd / start capital. The shadow is the same book WITHOUT the trades of the sessions after the first placement: shadow_net = net - trade_effect, where trade_effect = sum over the trades of side * units * (the latest close known - execution price) - fee, i.e. the same book without those trades up to today (exact: a trade only moves units and cash). Dividends, financing and splits are not separated here; the kinds: initial: the first session of the account; chosen: a trade on a session the model decided (its `decs`); forced: a trade of a model's account on a session it did not decide (the sale of what the rules no longer trade, a corporate action); rule: a trade of a rule-based account (a name with `_` or a variant tag), mechanical by its rule, nobody chooses it; the first placement is the first session WITH trades, not the account's start date, and a rule-based account's first placement is `initial` too, its later trades `rule`", "total": { "accounts": 139, "accounts_better_than_shadow": 1, "accounts_worse_than_shadow": 11, "fees_usd": 10043.1, "trade_effect_usd": -1471.86 } }, "power": { "alpha": 0.05, "forecasts_per_session": 12, "formula": "forecasts = ((z_a*sqrt(p0 q0) + z_b*sqrt(p1 q1))/(p1-p0))^2; sessions = forecasts * (1+(k-1)*rho) / k", "headline": { "months": 10.0, "p_true": 0.55, "rho": 0.2, "sessions": 209, "simulated_power": 0.815, "simulation": "1000 trials, hit chance of a session ~ Beta, k=12, cluster-robust z-test" }, "power": 0.8, "question": "sessions needed to tell a 55% hit rate from a coin (50%)", "rho_measured": null, "rho_measured_from_sessions": 20, "rho_measured_sessions": 3, "rho_source": "assumed (fewer than 5 sessions in the book)", "rho_used_for_headline": 0.2, "sessions_in_book": 3, "table": [ { "months": 8.6, "p_true": 0.53, "rho": 0.0, "sessions": 182 }, { "months": 3.1, "p_true": 0.55, "rho": 0.0, "sessions": 66 }, { "months": 0.8, "p_true": 0.6, "rho": 0.0, "sessions": 17 }, { "months": 13.4, "p_true": 0.53, "rho": 0.05, "sessions": 282 }, { "months": 4.8, "p_true": 0.55, "rho": 0.05, "sessions": 102 }, { "months": 1.2, "p_true": 0.6, "rho": 0.05, "sessions": 26 }, { "months": 18.1, "p_true": 0.53, "rho": 0.1, "sessions": 382 }, { "months": 6.5, "p_true": 0.55, "rho": 0.1, "sessions": 137 }, { "months": 1.6, "p_true": 0.6, "rho": 0.1, "sessions": 34 }, { "months": 27.7, "p_true": 0.53, "rho": 0.2, "sessions": 581 }, { "months": 9.9, "p_true": 0.55, "rho": 0.2, "sessions": 209 }, { "months": 2.5, "p_true": 0.6, "rho": 0.2, "sessions": 52 }, { "months": 37.2, "p_true": 0.53, "rho": 0.3, "sessions": 781 }, { "months": 13.4, "p_true": 0.55, "rho": 0.3, "sessions": 281 }, { "months": 3.3, "p_true": 0.6, "rho": 0.3, "sessions": 70 }, { "months": 56.2, "p_true": 0.53, "rho": 0.5, "sessions": 1180 }, { "months": 20.2, "p_true": 0.55, "rho": 0.5, "sessions": 424 }, { "months": 5.0, "p_true": 0.6, "rho": 0.5, "sessions": 106 } ], "trading_days_per_month": 21, "two_sided": true }, "power_brier": { "alpha": 0.05, "at_sessions": { "126": { "min_difference": 0.0114, "tells_a_brier_below": 0.2386 }, "52": { "min_difference": 0.0178, "tells_a_brier_below": 0.2322 } }, "forecasts_per_session": 12, "formula": "sessions = ((z_a + z_b) sd / delta)^2 x (1 + (k-1) rho) / k; delta_min = (z_a + z_b) sd sqrt((1 + (k-1) rho) / (k sessions))", "power": 0.8, "question": "the smallest Brier drop below the coin (0.25) that can be told from it", "reference": 0.25, "rho_losses": 0.43, "rho_source": "proxy: the measured mean correlation of the seats' probabilities (n_eff), until 5 sessions", "sd_loss": 0.0662, "sd_source": "measured on the book (262 forecasts of the seats)", "sessions_for_difference": [ { "difference": 0.005, "months": 31.3, "sessions": 658 }, { "difference": 0.01, "months": 7.8, "sessions": 165 }, { "difference": 0.02, "months": 2.0, "sessions": 42 }, { "difference": 0.03, "months": 0.9, "sessions": 19 }, { "difference": 0.05, "months": 0.3, "sessions": 7 } ], "simulated_power_at_min_difference": { "power": 0.783, "sessions": 52, "trials": 1000 }, "two_sided": true }, "ranks": { "horizons": { "1d": { "basis": "№450: the 1d place, its interval and the 30/10 count are all on the forecasts of the main Brier: a row with `pall` (from 2026-10-21) - every forecast of the shared event, a stated 50% and a draw included; an earlier row - the stated forecasts `p` + `p50` (a stated 50% included), a draw out, as those days were published (the same cells as the pairs)", "block": 1, "rows": [], "unit": "session" }, "1m": { "block": 21, "needs_1d_rank": true, "rows": [], "unit": "run" }, "1w": { "block": 5, "needs_1d_rank": true, "rows": [], "unit": "run" }, "6m": { "block": 126, "descriptive": true, "descriptive_note": "descriptive: the six-month outcomes overlap (126 sessions each) and are few, so the number is shown without an interval and is not a test of who is better", "needs_1d_rank": true, "rows": [], "unit": "run" } }, "level": 0.95, "rank_after": 30, "rank_days": 10, "resamples": 2000, "rule": "A model is ranked after 30 resolved forecasts on at least 10 trading days (thresholds rank_after, rank_days) - counted BY HORIZON, and the first rank is the 1d one: a model gets a 1w / 1m / 6m place only once it has its 1d place and the horizon's own 30 forecasts on 10 runs. Places are shared on equal Brier (1, 1, 3). Every place comes with an interval (rank_lo - rank_hi, 95%) from resampling the sessions (1d) or runs in blocks of the horizon's sessions (1w / 1m / 6m) and re-ranking all models each time; models whose interval reaches the group leader's place form one tie group (tie_group) - they are not told apart by this sample." }, "sample": { "bootstrap_from_sessions": 20, "first_session": "2026-10-19", "last_session": "2026-10-21", "min_sessions_for_interval": 5, "note": "an interval appears from 5 scored sessions (Student t on the sessions' means, approximate), from 20 by the bootstrap by sessions; the 12 indicators of a day are one cluster", "runs_with_answers": 7, "scored_sessions": 3 }, "seed": 20261019, "sharpness": { "climatology_sha256": "2810d11e907bbaa1f311d06622c929c69e60cc81e558fdb78f5baa04113cabb7", "consensus": { "1d": { "calibration": { "calibration_slope": -4.959, "calibration_slope_ols": -3.566, "logit_intercept": 0.964, "n": 34, "share_up": 64.7, "slope_se": 2.71, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 5.05, "n": 48, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 50.5, "n": 48, "sharpness_pp": 4.71 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 9.83, "n": 48, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 52.1, "n": 48, "sharpness_pp": 4.58 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 7.44, "n": 48, "p_up": 54.7, "sharpness_pp": 6.11 }, "mean_p": 52.1, "n": 48, "sharpness_pp": 5.34 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 12.71, "n": 48, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 53.0, "n": 48, "sharpness_pp": 9.95 } } }, "crowd_questions": 15, "crowd_what": "vs_crowd: see its `rule`. vs_crowd_pairs: shrink against the crowd on the same questions: the model's own answer to the crowd's question against the crowd's price at that minute; sharpness_pp and crowd_sharpness_pp = mean |p-50|; ratio = their quotient; shrink_pp = crowd minus model; slope_through_50 = slope of (p-50) on (crowd-50) through the origin; null under 5 questions", "horizons": [ "1d", "1w", "1m", "6m" ], "min_slope_n": 30, "models": { "chatgpt": { "1d": { "calibration": { "calibration_slope": -3.53, "calibration_slope_ols": -2.997, "logit_intercept": 0.62, "n": 34, "share_up": 64.7, "slope_se": 2.012, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 6.47, "n": 48, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 49.2, "n": 48, "sharpness_pp": 5.58 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 12.53, "n": 48, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 50.9, "n": 48, "sharpness_pp": 7.23 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 9.66, "n": 48, "p_up": 54.7, "sharpness_pp": 6.11 }, "mean_p": 51.7, "n": 48, "sharpness_pp": 7.62 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 14.32, "n": 48, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 51.7, "n": 48, "sharpness_pp": 11.58 } } }, "claude": { "1d": { "calibration": { "calibration_slope": -5.298, "calibration_slope_ols": -4.386, "logit_intercept": 0.469, "n": 34, "share_up": 64.7, "slope_se": 3.333, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 3.57, "n": 48, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 49.3, "n": 48, "sharpness_pp": 2.35 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 7.02, "n": 48, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 51.9, "n": 48, "sharpness_pp": 5.23 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 4.27, "n": 48, "p_up": 54.7, "sharpness_pp": 6.11 }, "mean_p": 51.3, "n": 48, "sharpness_pp": 2.67 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 15.42, "n": 48, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 50.3, "n": 48, "sharpness_pp": 10.94 } } }, "deepseek": { "1d": { "calibration": { "calibration_slope": -0.388, "calibration_slope_ols": -0.367, "logit_intercept": 0.63, "n": 34, "share_up": 64.7, "slope_se": 1.831, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 5.32, "n": 48, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 50.8, "n": 48, "sharpness_pp": 4.67 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 9.33, "n": 48, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 54.0, "n": 48, "sharpness_pp": 6.52 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 7.46, "n": 47, "p_up": 55.0, "sharpness_pp": 6.07 }, "mean_p": 51.6, "n": 47, "sharpness_pp": 5.13 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 12.32, "n": 48, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 54.2, "n": 48, "sharpness_pp": 8.23 } } }, "gemini": { "1d": { "calibration": { "calibration_slope": -3.673, "calibration_slope_ols": -2.379, "logit_intercept": 1.314, "n": 34, "share_up": 64.7, "slope_se": 2.087, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 8.4, "n": 47, "p_up": 51.5, "sharpness_pp": 3.83 }, "mean_p": 53.2, "n": 47, "sharpness_pp": 8.45 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 12.39, "n": 47, "p_up": 58.6, "sharpness_pp": 9.75 }, "mean_p": 56.7, "n": 47, "sharpness_pp": 10.51 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 10.62, "n": 47, "p_up": 54.7, "sharpness_pp": 6.13 }, "mean_p": 56.1, "n": 47, "sharpness_pp": 10.72 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 10.98, "n": 47, "p_up": 65.5, "sharpness_pp": 16.85 }, "mean_p": 56.2, "n": 47, "sharpness_pp": 12.66 } } }, "grok": { "1d": { "calibration": { "calibration_slope": 0.624, "calibration_slope_ols": 0.543, "logit_intercept": 0.59, "n": 34, "share_up": 64.7, "slope_se": 1.399, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 7.6, "n": 48, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 49.5, "n": 48, "sharpness_pp": 6.92 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 10.27, "n": 48, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 49.7, "n": 48, "sharpness_pp": 5.71 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 8.19, "n": 48, "p_up": 54.7, "sharpness_pp": 6.11 }, "mean_p": 50.7, "n": 48, "sharpness_pp": 7.0 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 15.05, "n": 48, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 51.3, "n": 48, "sharpness_pp": 9.04 } } }, "kimi": { "1d": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 11, "share_up": 54.5, "slope_se": null, "slope_why_null": "under 30 forecasts with an outcome (n=11)" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 3.2, "n": 12, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 50.2, "n": 12, "sharpness_pp": 5.33 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 9.18, "n": 10, "p_up": 60.0, "sharpness_pp": 11.31 }, "mean_p": 53.8, "n": 10, "sharpness_pp": 5.8 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 4.05, "n": 11, "p_up": 55.0, "sharpness_pp": 6.56 }, "mean_p": 53.5, "n": 11, "sharpness_pp": 8.27 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 11.85, "n": 11, "p_up": 66.5, "sharpness_pp": 17.89 }, "mean_p": 54.6, "n": 11, "sharpness_pp": 11.36 } } }, "meta": { "1d": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 10, "share_up": 70.0, "slope_se": null, "slope_why_null": "under 30 forecasts with an outcome (n=10)" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 11.06, "n": 22, "p_up": 51.4, "sharpness_pp": 3.87 }, "mean_p": 52.1, "n": 22, "sharpness_pp": 11.41 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 13.97, "n": 22, "p_up": 58.7, "sharpness_pp": 9.86 }, "mean_p": 52.9, "n": 22, "sharpness_pp": 9.86 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 11.78, "n": 22, "p_up": 54.7, "sharpness_pp": 6.19 }, "mean_p": 53.3, "n": 22, "sharpness_pp": 9.45 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 12.73, "n": 22, "p_up": 65.3, "sharpness_pp": 16.66 }, "mean_p": 54.4, "n": 22, "sharpness_pp": 10.86 } } }, "mimo": { "1d": { "calibration": { "calibration_slope": -6.531, "calibration_slope_ols": -3.239, "logit_intercept": 1.198, "n": 33, "share_up": 63.6, "slope_se": 2.787, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 6.28, "n": 47, "p_up": 51.6, "sharpness_pp": 3.88 }, "mean_p": 49.7, "n": 47, "sharpness_pp": 5.87 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 12.65, "n": 45, "p_up": 59.3, "sharpness_pp": 10.14 }, "mean_p": 50.0, "n": 45, "sharpness_pp": 7.0 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 8.6, "n": 46, "p_up": 55.1, "sharpness_pp": 6.19 }, "mean_p": 51.4, "n": 46, "sharpness_pp": 6.3 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 13.29, "n": 48, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 53.2, "n": 48, "sharpness_pp": 15.21 } } }, "stepfun": { "1d": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 23, "share_up": 69.6, "slope_se": null, "slope_why_null": "under 30 forecasts with an outcome (n=23)" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 5.85, "n": 36, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 50.0, "n": 36, "sharpness_pp": 4.44 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 15.45, "n": 36, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 48.6, "n": 36, "sharpness_pp": 9.08 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 9.58, "n": 36, "p_up": 54.7, "sharpness_pp": 6.11 }, "mean_p": 50.1, "n": 36, "sharpness_pp": 5.97 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 15.32, "n": 36, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 51.6, "n": 36, "sharpness_pp": 4.81 } } }, "wenxin": { "1d": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 12, "share_up": 66.7, "slope_se": null, "slope_why_null": "under 30 forecasts with an outcome (n=12)" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 9.26, "n": 12, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 52.7, "n": 12, "sharpness_pp": 7.67 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 16.69, "n": 12, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 56.0, "n": 12, "sharpness_pp": 11.33 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 18.97, "n": 12, "p_up": 54.7, "sharpness_pp": 6.11 }, "mean_p": 51.4, "n": 12, "sharpness_pp": 15.08 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 9.45, "n": 12, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 57.2, "n": 12, "sharpness_pp": 13.83 } } }, "zai": { "1d": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 11, "share_up": 72.7, "slope_se": null, "slope_why_null": "under 30 forecasts with an outcome (n=11)" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 3.68, "n": 24, "p_up": 51.5, "sharpness_pp": 3.81 }, "mean_p": 52.6, "n": 24, "sharpness_pp": 4.54 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 10.45, "n": 24, "p_up": 58.6, "sharpness_pp": 9.71 }, "mean_p": 53.3, "n": 24, "sharpness_pp": 8.17 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 8.07, "n": 24, "p_up": 54.7, "sharpness_pp": 6.11 }, "mean_p": 53.7, "n": 24, "sharpness_pp": 7.0 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 13.71, "n": 24, "p_up": 65.6, "sharpness_pp": 16.9 }, "mean_p": 53.6, "n": 24, "sharpness_pp": 7.96 } } } }, "models_pooled": { "1d": { "calibration": { "calibration_slope": -1.856, "calibration_slope_ols": -1.612, "logit_intercept": 0.752, "n": 270, "share_up": 65.2, "slope_se": 0.553, "slope_why_null": null }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 6.34, "n": 392, "p_up": 51.5, "sharpness_pp": 3.83 }, "mean_p": 50.6, "n": 392, "sharpness_pp": 5.83 } }, "1m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 11.44, "n": 388, "p_up": 58.7, "sharpness_pp": 9.82 }, "mean_p": 52.1, "n": 388, "sharpness_pp": 7.55 } }, "1w": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 8.68, "n": 389, "p_up": 54.8, "sharpness_pp": 6.13 }, "mean_p": 52.1, "n": 389, "sharpness_pp": 7.01 } }, "6m": { "calibration": { "calibration_slope": null, "calibration_slope_ols": null, "logit_intercept": null, "n": 0, "share_up": null, "slope_se": null, "slope_why_null": "no forecasts with an outcome on this horizon yet" }, "sharpness": { "climatology": { "mean_distance_to_climatology_pp": 13.52, "n": 392, "p_up": 65.6, "sharpness_pp": 16.91 }, "mean_p": 53.0, "n": 392, "sharpness_pp": 10.53 } } }, "timely": "a probability (elicited or a stated 50) from a line sealed no later than the event's reference price, the issue's one event, the last such line of a cell", "vs_crowd": { "counted": { "cells": 151, "crowd_sharpness_pp_on_same_cells": 18.62, "models_sharpness_pp": 6.99, "ratio": 0.376, "runs": 3, "why_null": null }, "models": { "chatgpt": { "cells": 19, "crowd_sharpness_pp_on_same_cells": 18.84, "ratio": 0.349, "runs": 3, "sharpness_pp": 6.58, "shrink_pp": 12.26, "why_null": null }, "claude": { "cells": 19, "crowd_sharpness_pp_on_same_cells": 18.84, "ratio": 0.575, "runs": 3, "sharpness_pp": 10.84, "shrink_pp": 8.0, "why_null": null }, "deepseek": { "cells": 19, "crowd_sharpness_pp_on_same_cells": 18.84, "ratio": 0.176, "runs": 3, "sharpness_pp": 3.32, "shrink_pp": 15.53, "why_null": null }, "gemini": { "cells": 19, "crowd_sharpness_pp_on_same_cells": 18.84, "ratio": 0.528, "runs": 3, "sharpness_pp": 9.95, "shrink_pp": 8.89, "why_null": null }, "grok": { "cells": 19, "crowd_sharpness_pp_on_same_cells": 18.84, "ratio": 0.26, "runs": 3, "sharpness_pp": 4.89, "shrink_pp": 13.95, "why_null": null }, "kimi": { "cells": 6, "crowd_sharpness_pp_on_same_cells": 20.35, "ratio": 0.172, "runs": 1, "sharpness_pp": 3.5, "shrink_pp": 16.85, "why_null": null }, "meta": { "cells": 5, "crowd_sharpness_pp_on_same_cells": 14.0, "ratio": 1.057, "runs": 1, "sharpness_pp": 14.8, "shrink_pp": -0.8, "why_null": null }, "mimo": { "cells": 19, "crowd_sharpness_pp_on_same_cells": 18.84, "ratio": 0.33, "runs": 3, "sharpness_pp": 6.21, "shrink_pp": 12.63, "why_null": null }, "stepfun": { "cells": 13, "crowd_sharpness_pp_on_same_cells": 18.15, "ratio": 0.292, "runs": 2, "sharpness_pp": 5.31, "shrink_pp": 12.84, "why_null": null }, "wenxin": { "cells": 8, "crowd_sharpness_pp_on_same_cells": 20.74, "ratio": 0.307, "runs": 1, "sharpness_pp": 6.38, "shrink_pp": 14.36, "why_null": null }, "zai": { "cells": 5, "crowd_sharpness_pp_on_same_cells": 14.0, "ratio": 0.671, "runs": 1, "sharpness_pp": 9.4, "shrink_pp": 4.6, "why_null": null } }, "rule": "per run: the markets = Kalshi's with Polymarket's contract in place where a market is on both venues; the seats = those whose answer line was sealed (max(at, booked_at)) no later than the reference price (09:30 ET of the session); the cells = market x seat with a crowd_up answer; sharpness = the mean |p-50| over the cells (models: their crowd_up; crowd: the price of the cell's market), in points; the counted runs are pooled by cells. crowd_sharpness_pp of a run = over all its markets, crowd_sharpness_pp_on_same_cells = weighted by the cells", "runs": [ { "cells": 31, "counted": false, "crowd_sharpness_pp": 10.25, "markets": 4, "markets_asked": 4, "models_sharpness_on_same_cells_crowd_pp": 10.55, "models_sharpness_pp": 4.81, "ratio": 0.469, "run_id": "2026-10-18-radar", "seats": 8, "sources": { "kalshi": 0, "polymarket": 4 } }, { "cells": 42, "counted": true, "crowd_sharpness_pp": 20.35, "markets": 6, "markets_asked": 6, "models_sharpness_on_same_cells_crowd_pp": 20.35, "models_sharpness_pp": 6.98, "ratio": 0.343, "run_id": "2026-10-19-am", "seats": 7, "sources": { "kalshi": 1, "polymarket": 5 } }, { "cells": 64, "counted": true, "crowd_sharpness_pp": 20.74, "markets": 8, "markets_asked": 8, "models_sharpness_on_same_cells_crowd_pp": 20.74, "models_sharpness_pp": 5.92, "ratio": 0.286, "run_id": "2026-10-20-am", "seats": 8, "sources": { "kalshi": 2, "polymarket": 6 } }, { "cells": 45, "counted": true, "crowd_sharpness_pp": 14.0, "markets": 5, "markets_asked": 5, "models_sharpness_on_same_cells_crowd_pp": 14.0, "models_sharpness_pp": 8.53, "ratio": 0.61, "run_id": "2026-10-21-am", "seats": 9, "sources": { "kalshi": 1, "polymarket": 4 } }, { "cells": 63, "counted": false, "crowd_sharpness_pp": 26.57, "markets": 7, "markets_asked": 7, "models_sharpness_on_same_cells_crowd_pp": 26.57, "models_sharpness_pp": 16.05, "ratio": 0.604, "run_id": "2026-10-22-am", "seats": 9, "sources": { "kalshi": 2, "polymarket": 5 } } ] }, "vs_crowd_pairs": { "council": { "crowd_kalshi": { "crowd_sharpness_pp": 27.96, "n": 5, "ratio": 0.273, "sharpness_pp": 7.64, "shrink_pp": 20.32, "slope_through_50": 0.236, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 14.89, "n": 10, "ratio": 0.362, "sharpness_pp": 5.39, "shrink_pp": 9.49, "slope_through_50": 0.243, "why_null": null } }, "models": { "chatgpt": { "crowd_kalshi": { "crowd_sharpness_pp": 29.3, "n": 5, "ratio": 0.3, "sharpness_pp": 8.8, "shrink_pp": 20.5, "slope_through_50": 0.287, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 14.95, "n": 10, "ratio": 0.281, "sharpness_pp": 4.2, "shrink_pp": 10.75, "slope_through_50": 0.068, "why_null": null } }, "claude": { "crowd_kalshi": { "crowd_sharpness_pp": 25.1, "n": 5, "ratio": 0.614, "sharpness_pp": 15.4, "shrink_pp": 9.7, "slope_through_50": 0.604, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 14.0, "n": 10, "ratio": 0.571, "sharpness_pp": 8.0, "shrink_pp": 6.0, "slope_through_50": 0.548, "why_null": null } }, "deepseek": { "crowd_kalshi": { "crowd_sharpness_pp": 28.78, "n": 5, "ratio": 0.146, "sharpness_pp": 4.2, "shrink_pp": 24.58, "slope_through_50": 0.079, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 14.25, "n": 10, "ratio": 0.274, "sharpness_pp": 3.9, "shrink_pp": 10.35, "slope_through_50": 0.105, "why_null": null } }, "gemini": { "crowd_kalshi": { "crowd_sharpness_pp": 29.12, "n": 5, "ratio": 0.316, "sharpness_pp": 9.2, "shrink_pp": 19.92, "slope_through_50": 0.176, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 15.25, "n": 10, "ratio": 0.584, "sharpness_pp": 8.9, "shrink_pp": 6.35, "slope_through_50": 0.366, "why_null": null } }, "grok": { "crowd_kalshi": { "crowd_sharpness_pp": 29.06, "n": 5, "ratio": 0.289, "sharpness_pp": 8.4, "shrink_pp": 20.66, "slope_through_50": 0.239, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 14.25, "n": 10, "ratio": 0.337, "sharpness_pp": 4.8, "shrink_pp": 9.45, "slope_through_50": 0.2, "why_null": null } }, "meta": { "crowd_kalshi": { "crowd_sharpness_pp": null, "n": 2, "ratio": null, "sharpness_pp": null, "shrink_pp": null, "slope_through_50": null, "why_null": "under 5 questions answered (n=2)" }, "crowd_polymarket": { "crowd_sharpness_pp": null, "n": 3, "ratio": null, "sharpness_pp": null, "shrink_pp": null, "slope_through_50": null, "why_null": "under 5 questions answered (n=3)" } }, "mimo": { "crowd_kalshi": { "crowd_sharpness_pp": 27.08, "n": 5, "ratio": 0.258, "sharpness_pp": 7.0, "shrink_pp": 20.08, "slope_through_50": 0.166, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 15.5, "n": 10, "ratio": 0.329, "sharpness_pp": 5.1, "shrink_pp": 10.4, "slope_through_50": 0.203, "why_null": null } }, "stepfun": { "crowd_kalshi": { "crowd_sharpness_pp": 28.76, "n": 5, "ratio": 0.264, "sharpness_pp": 7.6, "shrink_pp": 21.16, "slope_through_50": 0.138, "why_null": null }, "crowd_polymarket": { "crowd_sharpness_pp": 14.2, "n": 10, "ratio": 0.31, "sharpness_pp": 4.4, "shrink_pp": 9.8, "slope_through_50": 0.165, "why_null": null } }, "wenxin": { "crowd_kalshi": { "crowd_sharpness_pp": null, "n": 3, "ratio": null, "sharpness_pp": null, "shrink_pp": null, "slope_through_50": null, "why_null": "under 5 questions answered (n=3)" }, "crowd_polymarket": { "crowd_sharpness_pp": 17.83, "n": 6, "ratio": 0.374, "sharpness_pp": 6.67, "shrink_pp": 11.17, "slope_through_50": 0.235, "why_null": null } }, "zai": { "crowd_kalshi": { "crowd_sharpness_pp": null, "n": 2, "ratio": null, "sharpness_pp": null, "shrink_pp": null, "slope_through_50": null, "why_null": "under 5 questions answered (n=2)" }, "crowd_polymarket": { "crowd_sharpness_pp": null, "n": 4, "ratio": null, "sharpness_pp": null, "shrink_pp": null, "slope_through_50": null, "why_null": "under 5 questions answered (n=4)" } } } }, "vs_crowd_pairs_note": "vs_crowd_pairs = per model, the answer against the crowd price at the model's own minute, from the separate `crowd` lines (the pairs the Brier against the crowd uses; few so far); the main reading is vs_crowd, from the run lines", "what": "per model and horizon. sharpness (the TIMELY answers, no outcome needed - a long horizon that has not closed has its sharpness): sharpness_pp = the mean |p-50| in points; climatology = the fixed 2016-2025 window (council_clim_window) on the same answers: p_up = its share of up, sharpness_pp = its own distance from 50, mean_distance_to_climatology_pp = the model's mean |p - climatology| (so a far-from-50 six-month forecast is not read as overconfidence when the climatology itself is far). calibration (the issue's one event with an outcome, same_event true, counted): calibration_slope = the slope b of the logistic regression of the outcome on logit(p) (1 = calibrated, below 1 = overconfident, above 1 = underconfident; p held in [1%,99%]; Newton-Raphson), calibration_slope_ols = the least-squares slope of the outcome on p; slope_se = the naive Wald error (the forecasts of a session are not independent, so it is too small); null from fewer than 30 forecasts with the n kept" }, "snapshot_id": "ab060237f6bc02d1c9a6180877ca48ee1085a5db9064b5b3f17eca3785d726f3", "snapshot_run": "2026-10-22-am", "sources": { "agreement_by_shared_link": { "agree_not_sharing": 0.491, "agree_sharing": 0.521, "diff_within_strata": 0.05, "p_permutation": 0.518, "pairs": 2476, "pairs_sharing": 48, "strata": 34 }, "agreement_by_shared_site": { "agree_not_sharing": 0.49, "agree_sharing": 0.493, "diff_within_strata": -0.013, "p_permutation": 0.584, "pairs": 2476, "pairs_sharing": 673, "strata": 83 }, "answers": 707, "answers_without_links": 24, "citations": 1584, "joint_errors": { "note": "P(second wrong | first wrong) for pairs of seats on one indicator", "other_site": { "both_wrong_pct": 75.7, "first_wrong": 803 }, "shared_site": { "both_wrong_pct": 77.2, "first_wrong": 228 } }, "links_cited_by_2plus_seats": 30, "links_in_open_data": "api/v1/council-forecasts.csv columns source_domains, source_urls", 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