{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005148497,0.0002653474,0.0002394192,0.0001359406,0.0001517922,0.00012335,0.0004738172,0.0002237796,0.00004235052],"category_scores_gemma":[0.0001149695,0.0002619303,0.0001185096,0.00005493863,0.0001813256,0.000006205878,0.00008639161,0.0008675734,0.00003883421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005556681,"about_ca_system_score_gemma":0.0002858056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001566139,"about_ca_topic_score_gemma":0.000001717542,"domain_scores_codex":[0.9978139,0.0006180106,0.0007793319,0.0003375821,0.0002520935,0.0001990508],"domain_scores_gemma":[0.9975293,0.00001594064,0.001379322,0.0005350008,0.0004159731,0.0001244258],"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":[0.00001098473,0.00001852562,0.002912934,0.0000453515,0.0002189172,0.00001930821,0.0001391093,0.0001131727,0.1292791,0.000003790758,0.8606883,0.0065505],"study_design_scores_gemma":[0.000723686,0.0007490389,0.1417439,0.00005165458,0.0002090471,0.0001215179,0.00008943012,0.00003075913,0.004093846,0.0001064794,0.851616,0.0004647164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9661928,0.01018041,0.001204639,0.01948364,0.0006949005,0.0002903644,0.00008663046,0.000009304938,0.001857323],"genre_scores_gemma":[0.9223056,0.01189235,0.004071685,0.04550019,0.01392186,0.000008935778,0.000470537,0.0002415985,0.001587223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1388309,"threshold_uncertainty_score":0.9999833,"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."}}