{"id":"W4293205487","doi":"10.2139/ssrn.4060776","title":"Validation of the BOADICEA  Multifactorial Breast Cancer Risk Prediction Model in a Large Prospective Study","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"AI in cancer detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Breast cancer; Medicine; Cancer; Prospective cohort study; Risk assessment; Environmental health; Internal medicine; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02379625,0.001088058,0.0009233226,0.001064919,0.001022691,0.00136051,0.001756108,0.0009260508,0.002771043],"category_scores_gemma":[0.03383526,0.0005024754,0.001510922,0.001030651,0.0006367884,0.0008341622,0.001809438,0.001309019,0.0009401235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006134286,"about_ca_system_score_gemma":0.002234383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01086997,"about_ca_topic_score_gemma":0.008195097,"domain_scores_codex":[0.9939506,0.004419199,0.0003021511,0.0007548841,0.0004125519,0.000160583],"domain_scores_gemma":[0.979344,0.01492599,0.000939246,0.002217412,0.001846739,0.0007266449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003879871,0.0006320497,0.9652192,0.00007079184,0.001241035,0.00008557436,0.0002192407,0.004647347,0.0004364124,0.000370298,0.001563312,0.02163492],"study_design_scores_gemma":[0.001462269,0.003471758,0.8618948,0.0001202284,0.002578732,0.0005638432,0.000667022,0.1224047,0.0009740845,0.001681017,0.004096626,0.00008484634],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842235,0.0003617312,0.01080141,0.0003517749,0.00008778316,0.0002127458,0.003201076,0.00009365319,0.0006663655],"genre_scores_gemma":[0.9893135,0.0001037136,0.006506087,0.00006772509,0.00003895799,0.0002906226,0.003273214,0.00003226197,0.0003739383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02379625,"threshold_uncertainty_score":0.1258482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009584734804327042,"score_gpt":0.2579348616266385,"score_spread":0.2483501268223115,"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."}}