Prospect

A model writes a confident list of disease genes in a second. I checked those lists against a frozen human CD4+ T-cell CRISPRi screen the model can't recompute. The data contradicts almost half of the confident major-regulator calls. That's 46 out of 96, a 47.9 percent contradiction rate, with a 95 percent confidence interval running from 38 to 58. A fresh Claude Opus 4.8 run comes in at 51.7. The wrong calls land on famous genes rather than the biology, at permutation p 0.0001, and how sure the model says it is tells you nothing about whether it's right. Prospect checks a claim after the model makes it and before anyone believes it. It types each gene as a driver, a passenger, contradicted, or not assayed, hands back a signed receipt, and marks every result accepted=false until a person signs it with an Ed25519 key. No model can sign. A model has accepted zero records. Once AI writes most of the candidate work, the hard part is no longer producing claims. It's deciding which ones to keep. Reproducing a result is not the same as verifying it. Prospect is a small working version of the record science needs, where the data decides what counts and the next person starts from a judgment already made instead of remaking it.