CASP — Critical Assessment of Structure Prediction

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The blind, biennial community experiment that has assessed protein structure prediction since 1994, and the reason the AlphaFold claim is the best-evidenced capability claim in machine learning. Its design is the point: experimental structures that have been solved but not published are held back by their determining laboratories, predictors submit models against sequence alone with no access to the answer, and independent assessors score the submissions afterwards. A predictor cannot train on the test set, cannot tune against the leaderboard, and cannot choose which targets to be measured on. That is exactly the set of protections that public machine-learning benchmarks lack, and CASP14 in late 2020 is where AlphaFold2 produced accuracy that assessors described as competitive with experiment. Not a place: CASP is an experiment and a community, run through a coordinating centre rather than a building.

A node is not a place. Drawing it on a map would assert something about the world that no stored fact supports.