Evidence behind the measured results

Every number in the repo README's "Measured results" has a file here.

Claim	File
Gate 0: 90 of 98 lines on 9 public receipt photos (Spark), arithmetic 7 of 7	GATE-0-REPORT.md
Wonder 97 of 98 vs Spark 92 of 98 on the same set (Wonder after hand adjudication; Spark on the automatic scorer, which gives Wonder 86 of 98), latency and cost	WONDER-EVAL.md
Staple judge precision 0.79 (41 of 52) against a cadence proxy	JUDGE-EVAL.md

Read the numbers as a gap, not a score. Spark scored 90 of 98 in the Gate 0 run and 92 of 98 in the Wonder comparison on the same set. That difference is run-to-run variance on one small set. So quote the gap between the models, not either number alone. The live reader (auto: Spark first, Wonder re-reads a flagged receipt) is not yet measured on photos. A swapped pair of prices keeps the sum, so the review queue stays. On the judge playbook's sample receipt of the time (India Bazaar, Nov 1, 2026), three live runs on 2026-11-02 matched every printed price. One of them was re-read by Muse Wonder.

gate0-public-set/ holds the hand labels (written before any decode), the raw model results, the scores, the two scripts (decode_public.py, score_public.py) and manifest.json with each photo's public source. The photos themselves are not copied here, because they belong to their publishers. manifest.json links each one.

The scripts and reports were written in a separate workspace, so paths such as ~/workspace/meta-hackathon-2026/ in them point there, not into this repo. The reports are dated records; the app has changed since.