{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04232003,0.0006572185,0.0005482876,0.0009728131,0.002913306,0.007210608,0.002930069,0.008958878,0.005700985],"category_scores_gemma":[0.06363319,0.0004111524,0.002489363,0.0009686158,0.005685311,0.003353699,0.007406558,0.009504109,0.001081401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01934243,"about_ca_system_score_gemma":0.1368234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2598977,"about_ca_topic_score_gemma":0.3092997,"domain_scores_codex":[0.9511253,0.02987993,0.001554213,0.001852466,0.01219604,0.003392114],"domain_scores_gemma":[0.952275,0.0226286,0.002521338,0.002868677,0.01473504,0.004971304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000161679,0.0004321467,0.009749033,0.00347744,0.0002451949,0.0005377682,0.01235697,0.002340621,0.001136821,0.2155967,0.3418479,0.4121177],"study_design_scores_gemma":[0.0001749597,0.000577543,0.01621769,0.00684911,0.0004936307,0.0005513608,0.005255643,0.001568271,0.002923471,0.05170102,0.9134922,0.0001951392],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004796994,0.01256853,0.02055931,0.8858722,0.003511467,0.0009486547,0.000436886,0.0001967189,0.07110923],"genre_scores_gemma":[0.1577576,0.03265441,0.09524301,0.6830575,0.005655286,0.002413148,0.0007058461,0.0001770194,0.02233619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2598977,"threshold_uncertainty_score":0.5167699,"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."}}