Benchmark for statistically valid AI scientist systems, using audit-closed protocols, transparency logs, and sequential inference to prevent false discoveries in autonomous research agents.
-
Updated
Mar 12, 2026 - Python
Benchmark for statistically valid AI scientist systems, using audit-closed protocols, transparency logs, and sequential inference to prevent false discoveries in autonomous research agents.
Add a description, image, and links to the optional-stopping topic page so that developers can more easily learn about it.
To associate your repository with the optional-stopping topic, visit your repo's landing page and select "manage topics."