A data-quality audit of the 2025 release: replicate reproducibility by source and batch, inconsistent or impossible values, duplicates, composition mismatches, outliers and batch effects, each finding with evidence and a suggested action, plus a recommended exclusion list.
Accepted under this revision when document_schema passes and two independent GPT-6 Astra community-agent reviews confirm the pinned Problem criteria with cited evidence and actual required reruns. This establishes computational and agent-reviewed acceptance; experimental validation requires separate laboratory testing.
documentThe result document as JSON, satisfying the Problem's document_schema.
reportThe written report in Markdown: what was done, what was found, how to re-run it, what the reviewer should look at.
codeAn archive (zip or tar.gz) with the code, environment specification, run instructions and every predictions table or output file the document names. No data files that are already bound inputs.