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Research

Three studies. Five deciders. 2.3 million decisions.

Each one tests whether a decider's past decisions can predict its future ones, on cases the model never saw. Every subject is public. Every test is blind. One returned nothing, and that is published too.

2,369,659Decisions tested
5Deciders
3Studies
1Published null result
Peer review — ICLRRestaurant awards — Michelin Guide31 Aug 2026

Predicting Judgment from Behavioral Exhaust

Reasons pulled from each decider's own published record, ranked twice: how often a reason is raised, and how much it moves the decision. The two rankings disagree. The second one predicts.

33,043 papers69,300 reviews19,000 restaurants a yearTested forward and backward
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0.973 Ranking accuracy reproducing Michelin stars from published reviews alone, with no score to lean on. 95% CI 0.970–0.975 · 93.4% of stars caught
Ball-and-strike calls — MLB umpires1 Sep 2026

Judgment Without Text

No language at all, and a target written into the rulebook that all 124 deciders aim at identically. A personal signature survives anyway, and it lives almost entirely in the contested calls.

2,205,584 pitches124 umpires15,107 games2020–2026
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16× Better than chance at naming an umpire from where they said yes and where they said no, and nothing else. 20% top-1 of ~80 peers · chance 1.2%
Drug approvals — FDACourt rulings — SCOTUSPeer review — ICLR30 Aug 2026

The Refusal Engine

One method, run identically against three unrelated deciders. A refusal is a stack of separable reasons, and the odds climb as they accumulate. On the third decider the signal was not in the public record, and the method returned nothing.

141,819 decisions448 rejection lettersRuleset frozen, scored once
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4% → 43% Rejection rate as independent reasons stack up, against a 5.5% base rate. FDA, n=5,946 applications