{"id":"W2065240124","doi":"10.1038/sj.ejhg.5200998","title":"Genetic information and life insurance: a ‘real’ risk?","year":2003,"lang":"en","type":"review","venue":"European Journal of Human Genetics","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Underwriting; Genetic discrimination; Life insurance; Actuarial science; Genetic testing; Genetic epidemiology; Business; Medical underwriting; Insurance policy; General insurance; Biology; Genetics; Income protection insurance; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009077164,0.0003372001,0.0007339809,0.0004570331,0.0002434926,0.0004696071,0.0004243989,0.00007075242,0.0001491338],"category_scores_gemma":[0.0001609491,0.0002478679,0.0002518079,0.0002269624,0.00006870171,0.0004177731,0.0001389962,0.0005553313,0.0005019918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001982849,"about_ca_system_score_gemma":0.00006314816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006669753,"about_ca_topic_score_gemma":0.000001405901,"domain_scores_codex":[0.997819,0.0002321956,0.001305326,0.0001298804,0.0002942201,0.0002193759],"domain_scores_gemma":[0.9972587,0.00002771663,0.002161895,0.000202049,0.0003075048,0.00004218414],"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":[0.000009657558,0.00003028769,0.0003460276,0.00524167,0.0001514333,0.00005101327,0.0001311798,0.00002154985,2.280016e-7,0.00004173001,0.007672273,0.986303],"study_design_scores_gemma":[0.0003403206,0.00009002139,0.0009802623,0.002043045,0.000525714,0.00006273214,0.00002455302,0.00001560005,8.808389e-8,0.00004429734,0.9955848,0.0002886041],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004520738,0.974641,0.0001171727,0.000003760851,0.0005414609,0.0002276968,0.000007783267,0.00001465444,0.01992577],"genre_scores_gemma":[0.002535947,0.995362,0.0001717111,0.0002967242,0.001440467,9.041271e-7,0.00001419409,0.00006399467,0.0001139948],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9879125,"threshold_uncertainty_score":0.9999974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1246494902876053,"score_gpt":0.2569260289194667,"score_spread":0.1322765386318614,"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."}}