{"id":"W1747210889","doi":"10.29173/alr97","title":"Potential for Genetic Discrimination in Access to Insurance: Is There a Dark Side to Increased Availability of Genetic Information?","year":2013,"lang":"en","type":"article","venue":"Alberta Law Review","topic":"Legal Systems and Judicial Processes","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Underwriting; Genetic discrimination; Actuarial science; Legislature; Medical underwriting; Business; Population; Private information retrieval; Genetic testing; Insurance policy; General insurance; Political science; Law; Medicine; Income protection insurance; Computer security; Computer science; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02756625,0.0002214597,0.0006852202,0.002024714,0.007673372,0.009511375,0.003211445,0.0149839,0.004692446],"category_scores_gemma":[0.0530639,0.0006198076,0.0007363731,0.001392156,0.03459874,0.005881615,0.005239885,0.01118505,0.0004521551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01459974,"about_ca_system_score_gemma":0.03333385,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2284009,"about_ca_topic_score_gemma":0.2619732,"domain_scores_codex":[0.97276,0.007872842,0.0007688033,0.002018786,0.01228055,0.00429909],"domain_scores_gemma":[0.9416128,0.04079808,0.004025549,0.00335339,0.007878749,0.002331354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001863895,0.00003213336,0.007764144,0.00004628523,0.00001712658,0.0009357425,0.006481512,0.0002115405,0.0004535956,0.9523881,0.01190086,0.01975034],"study_design_scores_gemma":[0.0001406946,0.0001273652,0.02534825,0.001734795,0.0001510942,0.002950653,0.01390129,0.001943263,0.001894598,0.6286601,0.3228813,0.0002665482],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.09399439,0.007236871,0.01245379,0.5819501,0.0007069694,0.00008205205,0.000145123,0.00009352078,0.3033372],"genre_scores_gemma":[0.8604084,0.002768442,0.004098267,0.1140802,0.0007388734,0.00005270033,0.00004784665,0.00003055342,0.01777477],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7715991,"threshold_uncertainty_score":0.4541429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0182991260174569,"score_gpt":0.3120985351544801,"score_spread":0.2937994091370232,"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."}}