{"id":"W2285793395","doi":"10.1200/jco.2012.30.27_suppl.51","title":"Estimation of additional MRI resources needed in British Columbia for screening high-risk women for breast cancer.","year":2012,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; B.C. Women's Hospital & Health Centre; BC Cancer Agency","funders":"","keywords":"Medicine; Breast cancer; Mammography; Family history; Gynecology; Estimation; Population; Breast cancer screening; Breast MRI; Lifetime risk; Family medicine; Demography; Cancer; Obstetrics; Environmental health; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007957204,0.0002853756,0.0002463944,0.0008844155,0.0005082013,0.000665135,0.001027711,0.0003209029,0.002419068],"category_scores_gemma":[0.004280616,0.0003546162,0.0002591914,0.001553864,0.0001771413,0.0002690822,0.0004696881,0.0003877571,0.0003602149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008790049,"about_ca_system_score_gemma":0.005737127,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.928859,"about_ca_topic_score_gemma":0.9336529,"domain_scores_codex":[0.9994537,0.0001528249,0.0000451393,0.00008050771,0.0001664437,0.0001013831],"domain_scores_gemma":[0.9982578,0.0004922113,0.0002779796,0.00006729204,0.000680627,0.0002241526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002288554,0.0001202119,0.9675471,0.0001110614,0.00006288075,0.0002533391,0.0004361208,0.005050084,0.0003108576,0.0002650597,0.003165863,0.02244864],"study_design_scores_gemma":[0.00002466684,0.00007242973,0.9815383,0.00003291672,0.00003463273,0.00009742806,0.001506363,0.01485815,0.0001811387,0.0001171156,0.00152469,0.00001216651],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905619,0.0001874092,0.0004964923,0.0002062898,0.000003276358,0.0000968607,0.00518659,0.00002889156,0.003232262],"genre_scores_gemma":[0.9921879,0.000196942,0.001506372,0.00006144568,0.000001926034,0.00008666734,0.003609426,0.000007386202,0.002342005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.071141,"threshold_uncertainty_score":0.1431199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03756156464595888,"score_gpt":0.4153957006641971,"score_spread":0.3778341360182382,"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."}}