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