{"id":"W4400582871","doi":"10.1016/j.patter.2024.101012","title":"The potential of self-supervised learning in embryo selection for IVF success","year":2024,"lang":"en","type":"article","venue":"Patterns","topic":"Reproductive Biology and Fertility","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Vector Institute","keywords":"Selection (genetic algorithm); Artificial intelligence; Computer science; Machine learning; Psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003673272,0.00005020645,0.00009826222,0.00003592643,0.00005224921,0.000007883879,0.00003790778,0.00005083535,0.00002667581],"category_scores_gemma":[0.00008507787,0.00003235485,0.0000539785,0.00008199996,0.00002408017,0.0000252128,0.00001262669,0.00015275,0.000003927261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002514762,"about_ca_system_score_gemma":0.00003524263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007770779,"about_ca_topic_score_gemma":0.00004524848,"domain_scores_codex":[0.9994719,0.00005612257,0.0001315078,0.0001775296,0.00005253133,0.0001104251],"domain_scores_gemma":[0.9997558,0.00007406641,0.0000177755,0.00008762371,0.00004938059,0.00001538174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009274137,0.00006713823,0.9247915,0.0003697752,0.00009127797,0.00000403301,0.0005604914,0.00002223036,0.05057295,0.00006631299,0.00005998129,0.02246694],"study_design_scores_gemma":[0.0003165421,0.0001818031,0.9775981,0.00004575469,0.00003760431,0.0000108226,0.0001066873,0.01142815,0.009209484,0.0001324688,0.0008956713,0.00003691839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953212,0.0003863923,0.00270158,0.0008388315,0.0003047478,0.0002633487,0.000003174729,0.0000503955,0.0001304022],"genre_scores_gemma":[0.9993515,0.0000433235,0.00005369253,0.00002295506,0.0001979576,0.00003106709,0.00001128478,0.000006773552,0.0002814602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05280664,"threshold_uncertainty_score":0.1319393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01487160538644856,"score_gpt":0.2901985578035543,"score_spread":0.2753269524171058,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}