{"id":"W1975774835","doi":"10.1038/ejhg.2013.228","title":"Life insurance: genomic stratification and risk classification","year":2013,"lang":"en","type":"letter","venue":"European Journal of Human Genetics","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre Hospitalier de l’Université de Montréal; McGill University","funders":"Canadian Institutes of Health Research; Ministero dello Sviluppo Economico; Cancer Research UK","keywords":"Life insurance; Underwriting; Context (archaeology); Multidisciplinary approach; Genomics; Actuarial science; Business; Biology; Sociology; Genetics; Genome; Social science","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":[0.00840137,0.0005247921,0.001159109,0.0008256123,0.002812493,0.003726854,0.00146332,0.03965402,0.002421936],"category_scores_gemma":[0.03817924,0.0004736793,0.0009388139,0.0009125741,0.006456793,0.004331798,0.002180608,0.0330158,0.001312524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00686224,"about_ca_system_score_gemma":0.004547659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01050512,"about_ca_topic_score_gemma":0.01346932,"domain_scores_codex":[0.9919459,0.004242934,0.0007864734,0.0008502373,0.001700724,0.0004736277],"domain_scores_gemma":[0.9837869,0.01216998,0.0008638952,0.0004708126,0.001779123,0.0009294443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001652989,0.00005711897,0.003985228,0.0001692139,0.00004100959,0.005834259,0.001183799,0.0004535765,0.0004954035,0.0478185,0.8705785,0.06921817],"study_design_scores_gemma":[0.0001351461,0.00009733075,0.005934608,0.0009677011,0.00005416916,0.009522518,0.001632327,0.002204298,0.000430409,0.1539823,0.8249146,0.0001247891],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0003810894,0.002005801,0.0003056526,0.9928929,0.003326121,0.000005629451,0.00002065906,0.000003758716,0.001058263],"genre_scores_gemma":[0.01872823,0.004649066,0.001350974,0.9172379,0.05415969,0.0000414741,0.00005067759,0.00001691401,0.003765],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03965402,"threshold_uncertainty_score":0.04978925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02674852941584071,"score_gpt":0.2605081952114546,"score_spread":0.2337596657956139,"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."}}