{"id":"W3087071305","doi":"10.1016/j.jsr.2020.09.003","title":"Impact of medical fitness to drive policies in preventing property damage, injury, and death from motor vehicle collisions in Ontario, Canada","year":2020,"lang":"en","type":"article","venue":"Journal of Safety Research","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Ministry of Transportation of Ontario","funders":"","keywords":"Poison control; Occupational safety and health; Injury prevention; Human factors and ergonomics; Population; Suicide prevention; Business; Engineering; Medicine; Computer security; Risk analysis (engineering); Environmental health; Actuarial science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001262468,0.0002611711,0.0005355924,0.0009904725,0.003632528,0.001763487,0.001745727,0.001068839,0.00242523],"category_scores_gemma":[0.007006299,0.0004509369,0.001053864,0.001534546,0.0009317749,0.0005106647,0.001330999,0.001530151,0.0001478114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06332093,"about_ca_system_score_gemma":0.1527985,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9985234,"about_ca_topic_score_gemma":0.9994479,"domain_scores_codex":[0.9976392,0.0003029368,0.0001739211,0.0001361477,0.0005555528,0.001192398],"domain_scores_gemma":[0.9932719,0.0005678955,0.0008103373,0.0001042981,0.002324752,0.002920717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007208117,0.0007162549,0.9692718,0.0002186972,0.0002418673,0.000182352,0.001703851,0.001359086,0.0001693543,0.0007791321,0.005990846,0.01864603],"study_design_scores_gemma":[0.0000733351,0.0001006479,0.9957446,0.0001318142,0.00007854018,0.00001992672,0.001783079,0.0004522597,0.00003757418,0.00004602785,0.001518093,0.00001412182],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797617,0.002738153,0.00008700802,0.005037682,0.00009705344,0.0001850077,0.002709892,0.00001354255,0.009369953],"genre_scores_gemma":[0.9947428,0.001326572,0.000165135,0.0005154161,0.00002507159,0.00004013259,0.0005471098,0.000004702648,0.002633191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06332093,"threshold_uncertainty_score":0.4594277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1375901706032203,"score_gpt":0.4833633439292742,"score_spread":0.345773173326054,"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."}}