{"id":"W2889951601","doi":"","title":"Divulgation de l’information génétique en assurances","year":2015,"lang":"fr","type":"article","venue":"The Canadian Bar Review","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Genetic testing; Actuarial science; Business; Scope (computer science); Duty; Personally identifiable information; Insurance policy; Legislator; Political science; Legislation; Law; Medicine; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04936478,0.0007231192,0.001235174,0.003044868,0.007995419,0.01123563,0.003696892,0.0185382,0.004809933],"category_scores_gemma":[0.05473767,0.0007507678,0.001226544,0.00207145,0.04324324,0.005688391,0.004016803,0.01660611,0.001431937],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0507027,"about_ca_system_score_gemma":0.07427303,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6034579,"about_ca_topic_score_gemma":0.4692628,"domain_scores_codex":[0.9266706,0.0270399,0.002797007,0.004935905,0.03315928,0.005397227],"domain_scores_gemma":[0.9285327,0.0380819,0.002948154,0.005875924,0.02201468,0.002546823],"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":[0.000011951,0.00001129322,0.0004310298,0.000102585,0.00001537613,0.0002277026,0.002556851,0.0002007796,0.0003188334,0.9471676,0.0350412,0.01391477],"study_design_scores_gemma":[0.00002633129,0.00002675914,0.001818455,0.001057717,0.00002963642,0.0003713804,0.0009178781,0.0005211953,0.0005209224,0.09252031,0.9021071,0.00008232614],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.008499008,0.05058395,0.01947409,0.5373622,0.005611777,0.0001687651,0.0002780386,0.0001954327,0.3778268],"genre_scores_gemma":[0.5273432,0.03733429,0.02485082,0.2951571,0.006407179,0.0003013163,0.0002204483,0.0001990933,0.1081866],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9492973,"threshold_uncertainty_score":0.7977548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03364302993294873,"score_gpt":0.309299732202726,"score_spread":0.2756567022697773,"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."}}