{"id":"W4238860990","doi":"10.1002/9780470015902.a0005206.pub2","title":"Insurance and Human Genetics: Insurance Market Perspective","year":2014,"lang":"en","type":"other","venue":"Encyclopedia of Life Sciences","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Auto insurance risk selection; Actuarial science; Adverse selection; Group insurance; Key person insurance; Insurance policy; Risk pool; Business; Casualty insurance; General insurance; Order (exchange); Economics; Income protection insurance; Finance","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":[0.0009056235,0.0004189512,0.0004095761,0.001202079,0.0008636407,0.003178908,0.0007825284,0.004171884,0.01233034],"category_scores_gemma":[0.001552845,0.0002251075,0.0006478056,0.0008000035,0.003899608,0.003613281,0.0009738545,0.002110391,0.0004915004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003926543,"about_ca_system_score_gemma":0.001503788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006770697,"about_ca_topic_score_gemma":0.0029916,"domain_scores_codex":[0.9993969,0.0002633185,0.00001046851,0.00007130224,0.0001440441,0.0001139211],"domain_scores_gemma":[0.9984686,0.00106633,0.0001371648,0.00005209522,0.0001441449,0.0001317677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005028127,0.0000171597,0.0002812887,0.00001633644,0.000005365032,0.0000881181,0.00005083529,0.002459168,0.00004931968,0.9942009,0.001425534,0.001400961],"study_design_scores_gemma":[0.00001326668,0.00002334912,0.0005824633,0.00005443028,0.000007312429,0.0001380836,0.0002032237,0.009791492,0.00003842544,0.9775977,0.01153986,0.0000104355],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.08176967,0.03053888,0.06722319,0.14316,0.0009567752,0.0000975891,0.0006610112,0.00008258076,0.6755103],"genre_scores_gemma":[0.961044,0.009736566,0.004238527,0.004159364,0.00124062,0.00006629226,0.00007536783,0.00001645209,0.01942283],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01233034,"threshold_uncertainty_score":0.04124904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02983143129975824,"score_gpt":0.2787827723254581,"score_spread":0.2489513410256998,"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."}}