{"id":"W2109900132","doi":"","title":"Revisiting Genetic Discrimination Issues in 2010: Policy Options for Canada","year":2010,"lang":"en","type":"article","venue":"TSpace","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of Toronto","funders":"Institute of Genetics; Canadian Institutes of Health Research; Genome Canada","keywords":"Genetic discrimination; Legislation; Legislature; Status quo; Political science; Incentive; Genetic testing; Convention; Business; Public economics; Economics; Law; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001239275,0.00007500897,0.00007759958,0.0001154561,0.0001246552,0.00009000288,0.0001047832,0.00003384703,0.0002397744],"category_scores_gemma":[0.0004056345,0.00006609874,0.00002043515,0.0001920961,0.00001340201,0.0001872241,0.00003696905,0.00009947388,0.00005221655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002761531,"about_ca_system_score_gemma":0.0000589775,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7636415,"about_ca_topic_score_gemma":0.6095595,"domain_scores_codex":[0.999495,0.000004182162,0.0001104976,0.0001197213,0.00008813621,0.0001824497],"domain_scores_gemma":[0.999733,0.00002308238,0.00005110435,0.0001007114,0.00008502127,0.000007104691],"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":[0.0002494661,0.0003472033,0.04662481,0.00300637,0.000090747,0.00004955811,0.00742248,0.002126902,0.0791049,0.251368,0.3834519,0.2261577],"study_design_scores_gemma":[0.00107207,0.00001862014,0.1429132,0.0002272769,0.00005532092,0.000004939112,0.002760508,0.06125119,0.001620647,0.005369021,0.7839526,0.0007546312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9487971,0.0001226005,0.0004888343,0.02497025,0.000783961,0.0004210773,0.000002547193,0.0000463911,0.02436723],"genre_scores_gemma":[0.9882062,0.00001004112,0.0005997562,0.001018711,0.001787244,0.00002222349,0.00002165619,0.00001404059,0.008320129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4005007,"threshold_uncertainty_score":0.397565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07881687365557176,"score_gpt":0.2974344366084074,"score_spread":0.2186175629528356,"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."}}