{"id":"W2048095477","doi":"10.1080/14636778.2010.528189","title":"Genetic discrimination in private insurance: global perspectives","year":2010,"lang":"en","type":"article","venue":"New Genetics and Society","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Genetic discrimination; Genetic testing; Population; Politics; Dilemma; Social insurance; State (computer science); Political science; Actuarial science; Public economics; Business; Economics; Law; Medicine; Biology; Genetics; Environmental health","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":[0.007200886,0.0002464386,0.0005010028,0.003131439,0.001879956,0.006990298,0.0005945626,0.002610563,0.008261922],"category_scores_gemma":[0.01237729,0.0001215147,0.0004325658,0.004361334,0.007509867,0.007075085,0.003445808,0.002111791,0.0002169764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002032049,"about_ca_system_score_gemma":0.001732217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004091692,"about_ca_topic_score_gemma":0.005231007,"domain_scores_codex":[0.9958166,0.001996919,0.0001356636,0.0002941687,0.0007449026,0.001011628],"domain_scores_gemma":[0.9810989,0.01345501,0.002451533,0.0008512337,0.001300933,0.0008424286],"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":[0.0001815018,0.0001008131,0.1242688,0.0003605312,0.0001060322,0.001004181,0.01718899,0.001859124,0.0004255321,0.6922014,0.01022947,0.1520736],"study_design_scores_gemma":[0.00004346824,0.000202309,0.2126427,0.001564133,0.0002010864,0.002262627,0.0682955,0.001661746,0.001087389,0.5223578,0.1895773,0.0001038712],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.4720218,0.04359416,0.004541218,0.255451,0.0003962448,0.00001944177,0.0005616267,0.00002458375,0.2233898],"genre_scores_gemma":[0.9853167,0.007502877,0.0003280485,0.005040454,0.0003636308,0.000008624736,0.00006576467,0.000008072681,0.00136583],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.008261922,"threshold_uncertainty_score":0.03808236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04261346759056526,"score_gpt":0.2325245699060395,"score_spread":0.1899111023154742,"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."}}