{"id":"W3216784922","doi":"10.1136/jmedgenet-2021-107904","title":"Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors","year":2021,"lang":"en","type":"article","venue":"Journal of Medical Genetics","topic":"Ovarian cancer diagnosis and treatment","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"FP7 Health; Medical Research Council; Canadian Institutes of Health Research; Rosetrees Trust; European Commission; University College London; Department of Health and Social Care; Cancer Research UK; Ministère de l'Économie, de la Science et de l'Innovation - Québec; Government of Canada; Fondation du cancer du sein du Québec; Barts Charity; National Institute for Health and Care Research; Genome Canada","keywords":"Epidemiology; Ovarian cancer; Epithelial ovarian cancer; Medicine; Risk assessment; Oncology; Gynecology; Internal medicine; Cancer; Biology; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006014318,0.0002222114,0.0007090699,0.00007477821,0.0001257756,0.00002573831,0.0001071221,0.0003189013,0.0002312571],"category_scores_gemma":[0.001154523,0.0001488592,0.0002033515,0.0001451361,0.0001771549,0.00003509357,0.00009610201,0.0008537901,0.000001851337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001373904,"about_ca_system_score_gemma":0.0008404902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001415065,"about_ca_topic_score_gemma":0.0000308861,"domain_scores_codex":[0.9971993,0.0003376371,0.000942189,0.0002869658,0.0009792653,0.0002546246],"domain_scores_gemma":[0.9974813,0.0004872258,0.0006985025,0.0001996394,0.0004163853,0.0007169689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001172248,0.0003660074,0.9230905,0.00005996171,0.000640262,0.0005907386,0.0002791281,0.01188432,0.000368351,0.00004534943,0.0008195843,0.06173858],"study_design_scores_gemma":[0.004065567,0.0008800672,0.8798076,0.0003381228,0.001227145,0.0006277532,0.0001911288,0.1087383,0.001012884,0.001582278,0.00138474,0.0001444705],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.970751,0.01282336,0.01195632,0.003531192,0.0005883359,0.0001491189,0.000153413,0.0000118042,0.00003540241],"genre_scores_gemma":[0.907617,0.06776525,0.02288586,0.0005980212,0.001080407,0.000006807672,0.000009946251,0.00002175332,0.00001499595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09685396,"threshold_uncertainty_score":0.6070302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04611423002428986,"score_gpt":0.3215792221976981,"score_spread":0.2754649921734082,"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."}}