{"id":"W4321469928","doi":"10.7554/elife.83662","title":"Development and evaluation of a live birth prediction model for evaluating human blastocysts from a retrospective study","year":2023,"lang":"en","type":"article","venue":"eLife","topic":"Reproductive Biology and Fertility","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Blastocyst; Live birth; Blastocyst Transfer; Receiver operating characteristic; Infertility; Convolutional neural network; Medicine; Andrology; Obstetrics; Biology; Artificial intelligence; Computer science; Gynecology; Machine learning; Pregnancy; Embryo; Embryogenesis","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002658091,0.0000803421,0.000201926,0.00006978076,0.0001164822,0.000002852342,0.00002566518,0.00005461618,0.00001197495],"category_scores_gemma":[0.0008399922,0.00006845393,0.00002562068,0.00009633623,0.00004236086,0.00003861625,0.00003427377,0.00007128181,0.000004444687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001213609,"about_ca_system_score_gemma":0.0001609813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002076096,"about_ca_topic_score_gemma":0.00004399453,"domain_scores_codex":[0.9987664,0.00009876456,0.0002617605,0.000362816,0.0004100343,0.0001002645],"domain_scores_gemma":[0.9990668,0.00003698404,0.0001008087,0.0001818226,0.0005784801,0.00003507478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00279061,0.0005809299,0.8775777,0.00006234054,0.0004819231,7.708599e-7,0.04652382,0.0006292251,0.0621345,0.00002064405,0.00016809,0.009029454],"study_design_scores_gemma":[0.001902007,0.0005924138,0.8069896,0.00002847256,0.0001458434,3.623357e-7,0.00156041,0.1856436,0.002631959,0.0004602837,0.000003969648,0.00004106381],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972381,0.00007154469,0.0004897725,0.00003101919,0.00006740792,0.001963808,0.00003178588,0.00005313876,0.00005341395],"genre_scores_gemma":[0.9978412,0.000001847309,0.001512437,0.00001177021,0.00008817244,0.000356356,0.00007066545,0.000008352199,0.0001091636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1850144,"threshold_uncertainty_score":0.279147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1605355505070276,"score_gpt":0.4091629705619638,"score_spread":0.2486274200549362,"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."}}