Public Release - 2026-07-02
Artifact: benchmark_reality_gap_review_packet_v1. This note keeps model scores, demos, and leaderboard claims attached to their test conditions before they are treated as real-world evidence.
Artifact
A model score is meaningful inside a benchmark distribution, task definition, scorer, sampling procedure, contamination control, and evaluation assumption. Removing those conditions turns evidence into a slogan. The review packet therefore records the score and the condition together.
Reality Gap
Production context adds permissions, latency, tool failures, adversarial inputs, dirty data, cost ceilings, legal ownership, maintenance, rollback, and edge cases. These are not footnotes. They are the conditions under which an AI system either becomes useful or automates the wrong thing.
Review
The claim becomes stronger when the failure distribution is visible, the accountability route is named, and counterexamples can force a boundary update. Without those fields, a leaderboard can become a procurement shortcut and an agent demo can become an unreviewed operating policy.
The public claim under review.
The benchmark, task family, data distribution, scorer, and sampling rule.
The controlled condition under which the score was obtained.
The gap between the test condition and the deployment context.
The observed or expected pattern of errors outside the benchmark setting.
The owner, rollback path, and review channel for operational failure.
The public route by which the claim can be narrowed, rejected, or repaired.
The scope change required after deployment evidence is inspected.
The recorded state: supported, narrowed, pending, or retired.