{"id":"W2480514246","doi":"10.1158/1538-7445.am2016-2598","title":"Abstract 2598: Predicting breast and ovarian cancer risks for BRCA1 and BRCA2 mutation carriers using polygenic risk scores","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quebec Rehabilitation Research Network","funders":"","keywords":"Breast cancer; Medicine; Ovarian cancer; Oncology; Hazard ratio; Population; Odds ratio; Internal medicine; BRCA mutation; Genetic model; Gynecology; Genetics; Cancer; Confidence interval; Biology; Environmental health; Gene","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":[0.00244833,0.0007334611,0.0004318731,0.001871979,0.0002883691,0.0006260683,0.0005641363,0.0004817547,0.002690098],"category_scores_gemma":[0.007414186,0.0002932232,0.001581865,0.001465294,0.0002329658,0.0003608463,0.0006362383,0.0004681029,0.0004094285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002179484,"about_ca_system_score_gemma":0.000271661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008723284,"about_ca_topic_score_gemma":0.005028605,"domain_scores_codex":[0.9986336,0.0006691163,0.0001159348,0.0003496806,0.0001392832,0.00009239619],"domain_scores_gemma":[0.9963204,0.001838112,0.000906293,0.0004834429,0.0002146016,0.0002371659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003767685,0.00003846166,0.9945856,0.000008663762,0.0004342596,0.00006973279,0.00002003539,0.001114568,0.0004010885,0.00005130674,0.0001519937,0.002747666],"study_design_scores_gemma":[0.00004669944,0.0002596459,0.9803287,0.00000726661,0.0003600386,0.0003409824,0.00004849527,0.01788152,0.000266411,0.0001893852,0.000258588,0.00001224353],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966794,0.00009114357,0.001786476,0.00002471692,0.000007873332,0.000020943,0.001158954,0.00002070376,0.0002098591],"genre_scores_gemma":[0.9963868,0.00004512687,0.001636259,0.000008969993,0.000008570271,0.00002812228,0.001543314,0.000008537965,0.0003343391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008723284,"threshold_uncertainty_score":0.01734501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07165886218957201,"score_gpt":0.4107038770476602,"score_spread":0.3390450148580882,"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."}}