The Reader’s Kit
Say an AI model “scores 43%”. Before you repeat that number, ask it eight questions. Each one below is a rule this program holds itself to, and each links to where it is set out in full.
A rate quoted bare is misquoted: the interval is the part that makes it evidence.
The narrow one compares week on week. Any claim about the model itself needs the wide one.
Gateway, serving provider, temperature, token budget, date. A rate belongs to a model measured a particular way.
A bank built from items models fail is adversarial by construction. Its failure rate is not a general error rate.
Two independent halves set a noise floor. A movement smaller than that gap is not reported.
No judge grades its own model family, and agreement is published against a floor. Agreement is not correctness.
Draws lost to truncation, refusal or unreadable output. Above 5%, the run is disqualified: what vanishes is never random.
Every published figure is registered with the SHA-256 of its sources, and every issue's fingerprint is printed on its PDF.
Try it yourself
The test, and a finished issue
The 45 public probes, each with its written pass criterion, one per line: bank_v1_2_public.jsonl. Run any of them on any model, and grade the answer against the criterion.
A finished issue, to read with the eight questions beside it: The Calibration Vol 004 (PDF). The archive has every issue.
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