{"id":"W3171810880","doi":"10.3390/jpm11060511","title":"Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation (PERSPECTIVE I&I)","year":2021,"lang":"en","type":"article","venue":"Journal of Personalized Medicine","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":133,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's College Hospital; Cancer Care Ontario; University of Ottawa; McGill University; University Health Network; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Lunenfeld-Tanenbaum Research Institute; Ministère de la Santé et des Services Sociaux (Québec); Canadian Agency for Drugs and Technologies in Health; Sunnybrook Health Science Centre; Sinai Health System; Université Laval; Public Health Ontario; University of Toronto","funders":"Centre Hospitalier Universitaire de Québec; University of Toronto; McGill University; Génome Québec; Genome Canada; Université Laval","keywords":"Overdiagnosis; Breast cancer; Medicine; Context (archaeology); Risk assessment; Cancer screening; Breast cancer screening; Population; Health care; Cancer prevention; Risk analysis (engineering); Gynecology; Cancer; Mammography; Environmental health; Computer science; Internal medicine; Computer security","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":[0.0007694162,0.0001260627,0.0004821116,0.0001602919,0.00008477813,0.00001472684,0.00002867312,0.00006197934,0.0001487439],"category_scores_gemma":[0.0002576999,0.00009624028,0.0001215392,0.0001917737,0.0001437216,0.0002383895,0.00001172327,0.0002010797,6.85799e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003027149,"about_ca_system_score_gemma":0.0002983845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000833758,"about_ca_topic_score_gemma":0.0003809872,"domain_scores_codex":[0.9985981,0.0001039339,0.0005161561,0.0001749101,0.0004782678,0.0001286242],"domain_scores_gemma":[0.997273,0.0001067262,0.0007050954,0.00006809721,0.001713338,0.000133764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.005859292,0.0001609522,0.1206605,0.0003647501,0.001002642,0.00002832636,0.014284,0.000003602356,0.5706083,0.001823754,0.0005688226,0.284635],"study_design_scores_gemma":[0.02544218,0.004132599,0.8829276,0.002622636,0.003106342,0.002179237,0.06366806,0.0002446709,0.0102825,0.003141341,0.002043956,0.0002089079],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9479257,0.009480784,0.03770775,0.004192721,0.0001866382,0.0003628785,0.0000354075,0.000005973058,0.0001021226],"genre_scores_gemma":[0.9880433,0.00485298,0.006291119,0.0001594696,0.0004534662,0.00001798073,0.00001200393,0.0000116778,0.0001580084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7622671,"threshold_uncertainty_score":0.3924565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05571451419934722,"score_gpt":0.436844720502044,"score_spread":0.3811302063026968,"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."}}