The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.
Results by year
20092025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
96 works in the cohort · of 4,299,418page 1 of 2
Labels cover 0 of 96 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.
Distilled predictions cover 96 of 96 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.
Ramires Alsamir Tibana, Ivo Vieira de Sousa Neto, Nuno Manuel Frade de Sousa, Wellington Martins dos Santos, Jonato Prestes, João Henrique Falk Neto +3 more
2022· article· en· BMC Sports Science Medicine and Rehabilitation· Medicine
Felipe J. Aidar, Ciro José Brito, Dihogo Gama de Matos, Levy Anthony S. de Oliveira, Raphael Fabrício de Souza, Paulo Francisco de Almeida‐Neto +8 more
2022· article· en· BMC Sports Science Medicine and Rehabilitation· Medicine