{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00182985,0.001020654,0.001208386,0.0008176667,0.000429633,0.0009042412,0.001434464,0.0009307466,0.003136745],"category_scores_gemma":[0.002685579,0.0004669326,0.001515446,0.0006053408,0.0003615709,0.0004825481,0.0008257354,0.0009356139,0.0004303656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001043464,"about_ca_system_score_gemma":0.001630113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03777583,"about_ca_topic_score_gemma":0.01840751,"domain_scores_codex":[0.9994565,0.0002261899,0.00002308964,0.0001555739,0.00005149119,0.00008723293],"domain_scores_gemma":[0.998423,0.001002841,0.0001436523,0.0000597514,0.0002731717,0.00009759754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001601225,0.00006541811,0.01154673,0.00003215375,0.000171972,0.000145667,0.0000306664,0.978044,0.0002638319,0.001063671,0.000559271,0.007916578],"study_design_scores_gemma":[0.00001178895,0.00002542233,0.001477868,0.000004552087,0.00004034747,0.00002234734,0.000005056517,0.9977292,0.00003049112,0.0005404928,0.000107177,0.000005145333],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7876707,0.001864724,0.2003385,0.001161954,0.0001135248,0.0001524924,0.00382188,0.0008466084,0.004029669],"genre_scores_gemma":[0.9817902,0.0003454365,0.01187085,0.0001212618,0.00004345372,0.0001397384,0.002258849,0.0000312665,0.003398949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03777583,"threshold_uncertainty_score":0.07511187,"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."}}