From ca54ec2fe16cb9b7f34fe565ba06b61a96ec2133 Mon Sep 17 00:00:00 2001 From: Lumi AI Workspace Date: Tue, 7 Jul 2026 00:29:17 +0700 Subject: [PATCH] docs: add leakage audit checklist --- docs/evidence/LEAKAGE_AUDIT_CHECKLIST.md | 73 ++++++++++++++++++++++++ 1 file changed, 73 insertions(+) create mode 100644 docs/evidence/LEAKAGE_AUDIT_CHECKLIST.md diff --git a/docs/evidence/LEAKAGE_AUDIT_CHECKLIST.md b/docs/evidence/LEAKAGE_AUDIT_CHECKLIST.md new file mode 100644 index 00000000..6d805b65 --- /dev/null +++ b/docs/evidence/LEAKAGE_AUDIT_CHECKLIST.md @@ -0,0 +1,73 @@ +# Leakage Audit Checklist + +OpenAMP Foundry should treat leakage as a first-order evidence risk. + +This checklist helps reviewers and contributors inspect whether a benchmark, scorer, dataset, or selection step is accidentally learning from information that would not be available in a real prospective decision. + +This document is about evidence hygiene only. It does not add biological protocols, candidate-generation instructions, or optimization objectives. + +## When to use + +Use this checklist when a PR adds or changes: + +- benchmark data; +- train/test splits; +- scoring or ranking logic; +- external predictor outputs; +- model cards; +- evidence certificates; +- shortlist or panel-selection rules; +- claims about improved performance. + +## Leakage questions + +A submission should answer the relevant questions below. + +1. **Duplicate leakage:** Are near-duplicate records split across evaluation boundaries? +2. **Family leakage:** Are closely related records split in a way that makes performance look stronger than prospective use? +3. **Label leakage:** Does any feature encode the target, source label, or curation decision? +4. **Time leakage:** Does the evaluation use information that would not have existed at the decision date? +5. **Source leakage:** Are records from the same database, paper, lab, or preprocessing pipeline appearing in both comparison sides in a misleading way? +6. **Selection leakage:** Were thresholds, filters, or candidate groups chosen after seeing evaluation results? +7. **Metric leakage:** Was the primary metric changed after observing which metric looked best? +8. **Review leakage:** Did human review influence the evaluation set before performance was reported? +9. **Novelty leakage:** Does a novelty check use references that include the object being evaluated or close derivatives? +10. **Generated-artifact leakage:** Are generated files reused as if they were independent evidence? + +## Minimum audit note + +```markdown +## Leakage audit + +**Artifact:** Benchmark, scorer, dataset, report, or selection step. + +**Evaluation boundary:** What is supposed to be independent from what? + +**Most plausible leakage path:** One concrete path. + +**Check performed:** Exact check, command, review method, or reason not checked. + +**Result:** no obvious leakage found | leakage found | inconclusive | not applicable. + +**Decision impact:** no change | claim narrowed | benchmark blocked | scorer exploratory | follow-up required. +``` + +## Reviewer guidance + +A reviewer does not need to prove leakage to ask for this audit. The submitter must show why the result is not obviously inflated by a preventable boundary failure. + +If the audit is inconclusive, the claim can still be useful, but it should not be promoted beyond the strength of the audit. + +## Agent guidance + +An agent should identify the evaluation boundary before reporting performance. + +If the boundary cannot be named, the result is not ready to carry a benchmark or ranking claim. + +## Acceptance test + +A leakage audit is useful when a skeptical reviewer can say: + +> I understand what was supposed to be independent, the most plausible way independence could fail, and what check was performed. + +If those three facts are missing, the result is not yet trustworthy.