{"id":"W4231200303","doi":"10.1002/9780470015902.a0005203.pub2","title":"Insurance and Genetic Information","year":2010,"lang":"en","type":"other","venue":"Encyclopedia of Life Sciences","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Underwriting; Actuarial science; Genetic testing; Pace; Auto insurance risk selection; Business; Population; Genetic discrimination; Key person insurance; Health insurance; Group insurance; Medical underwriting; Insurance policy; Economics; General insurance; Health care; Income protection insurance; Medicine; Environmental health; Economic growth","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":[],"consensus_categories":[],"category_scores_codex":[0.00009116897,0.0001103863,0.0001142803,0.0001113907,0.00004072742,0.00001152463,0.0002303638,0.000199331,0.0001198788],"category_scores_gemma":[0.0001468185,0.00009907923,0.00002414672,0.0001147867,0.0004555703,0.000005987057,0.0000727477,0.00007070402,0.000009826736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003136615,"about_ca_system_score_gemma":0.0003512629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008722038,"about_ca_topic_score_gemma":0.0001940059,"domain_scores_codex":[0.9993448,0.00001651481,0.0001737835,0.000186491,0.0001671956,0.0001112241],"domain_scores_gemma":[0.999522,0.00000805315,0.0002045075,0.0001851229,0.00003146568,0.00004884192],"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":[0.00001205189,0.00002687287,0.05433903,0.000194032,0.00005399654,5.153505e-7,0.0002551984,0.00005383821,0.003663725,0.0001236825,0.8762478,0.06502923],"study_design_scores_gemma":[0.0001102234,0.00006282508,0.01017058,0.0000186915,0.000005430618,0.000003149875,0.00003280421,0.000005540523,0.0004744743,0.00003995224,0.988942,0.0001343917],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0566082,0.007072655,0.000300469,0.0001106854,0.001037234,0.0002206056,0.0001029864,0.00001843775,0.9345287],"genre_scores_gemma":[0.3133412,0.1017026,0.1297637,0.002034438,0.005506779,0.0002367984,0.0002984241,0.0004269239,0.4466891],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4878396,"threshold_uncertainty_score":0.4040333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006423534439720079,"score_gpt":0.2480706403361119,"score_spread":0.2416471058963919,"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."}}