Code and data for the paper "Critical Values Robust to P-hacking"
FiveThirtyEight reader responses to a food frequency questionnaire (FFQ).
An adversarial AI referee for empirical economics: finds p-hacking, cherry-picking and specification search, then re-runs the result.
Why you shouldn't peek at significance levels to decide when to stop an experiment
Benchmark for statistically valid AI scientist systems, using audit-closed protocols, transparency logs, and sequential inference to prevent false discoveries in autonomous research agents.
LLM agent for p-hacking & selective-reporting risk screening in academic PDFs.
Will You Spot the Leaks? A Data Science Challenge When models fly too high: A perilous journey through data leakage
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