{"id":"W2562990444","doi":"10.1016/j.aap.2016.12.008","title":"Prevalence and trends of drugged driving in Canada","year":2016,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"Traffic Injury Research Foundation","funders":"Transport Canada; Public Health Agency of Canada; State Farm","keywords":"Injury prevention; Poison control; Demography; Case fatality rate; Occupational safety and health; Human factors and ergonomics; Suicide prevention; Medicine; Environmental health; Forensic engineering; Engineering; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004423806,0.0002949785,0.0003979495,0.003535317,0.002413243,0.001890065,0.001889976,0.0008662348,0.005108376],"category_scores_gemma":[0.002406989,0.0005144258,0.00101847,0.006549679,0.0008441849,0.0007754087,0.0008530206,0.001216914,0.0004387483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02544514,"about_ca_system_score_gemma":0.03047203,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955202,"about_ca_topic_score_gemma":0.9969087,"domain_scores_codex":[0.9986641,0.00005814377,0.0001389009,0.0001804887,0.0004608387,0.000497427],"domain_scores_gemma":[0.9946886,0.0001946501,0.001035086,0.00008293324,0.002658027,0.001340792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006687885,0.00004295835,0.9945896,0.00004014291,0.00005097821,0.00008062377,0.0004036497,0.0001070216,0.0001200322,0.000110654,0.001337817,0.00304983],"study_design_scores_gemma":[0.000003493403,0.00001722882,0.9977807,0.00003014685,0.00001599696,0.00008956048,0.001082555,0.0002385953,0.00003315603,0.00001412794,0.000684543,0.000009847515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812386,0.001983231,0.0000865901,0.0006686402,0.00002923797,0.00003720488,0.01201476,0.00003873867,0.003903062],"genre_scores_gemma":[0.9941587,0.00128117,0.0001083493,0.0001243481,0.000009579269,0.000009285397,0.002727281,0.000009897969,0.001571386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02544514,"threshold_uncertainty_score":0.1846184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03174926845799757,"score_gpt":0.3709966120686457,"score_spread":0.3392473436106481,"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."}}