{"id":"W4401029844","doi":"10.1139/facets-2023-0101","title":"Still using genetic data? A comparative review of Canadian life insurance application forms before and after the GNDA","year":2024,"lang":"en","type":"review","venue":"FACETS","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre","funders":"Genome Canada","keywords":"Life insurance; Actuarial science; Purchasing; Genetic discrimination; Genetic testing; Business; Medicine; Marketing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01821874,0.0004626989,0.001773347,0.008515888,0.0009892216,0.002574847,0.001800242,0.001372837,0.003050224],"category_scores_gemma":[0.0528306,0.0004163714,0.001476207,0.01372823,0.001262594,0.001159623,0.0009035754,0.001772309,0.0003617888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01883575,"about_ca_system_score_gemma":0.0714325,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4749686,"about_ca_topic_score_gemma":0.6879069,"domain_scores_codex":[0.9904535,0.002766661,0.001440114,0.0004976777,0.004490014,0.0003520974],"domain_scores_gemma":[0.9474565,0.02820603,0.004031966,0.0007935925,0.01851776,0.0009941286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002338808,0.00003351815,0.001709001,0.1473462,0.0007155939,0.0001439027,0.001251607,0.0001973774,0.0003892034,0.004927279,0.0488506,0.7942019],"study_design_scores_gemma":[0.0000667034,0.0001204086,0.01393768,0.2507844,0.002037657,0.0003351853,0.0006857842,0.00008748485,0.0002767372,0.0004597621,0.7311475,0.00006066098],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003812144,0.9958839,0.00006099011,0.00154485,0.0001642796,0.00004514287,0.0002610683,0.000003794755,0.001654761],"genre_scores_gemma":[0.004313489,0.9938242,0.0002679011,0.001037607,0.00006471365,0.00003843977,0.0002017218,0.000005007219,0.0002470404],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5250314,"threshold_uncertainty_score":0.9444079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1671044024652628,"score_gpt":0.425037386261917,"score_spread":0.2579329837966542,"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."}}