{"id":"W2044402979","doi":"10.1016/j.aap.2012.01.030","title":"Trends in alcohol-impaired driving in Canada","year":2012,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Transport Canada; Traffic Injury Research Foundation","funders":"","keywords":"Crash; Environmental health; Injury prevention; Poison control; Human factors and ergonomics; Drunk drivers; Occupational safety and health; Suicide prevention; Driving under the influence; Demography; Population; Transport engineering; Medicine; Forensic engineering; Drunk driving; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000284919,0.000115207,0.0002335366,0.0006163475,0.00001964222,0.00001134455,0.0001009799,0.00004692552,0.0005118537],"category_scores_gemma":[0.000007029583,0.0001207302,0.0001468179,0.00151973,0.000003062688,0.0002888716,0.00001637149,0.0001140556,0.000009108462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004845185,"about_ca_system_score_gemma":0.00003045941,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3354836,"about_ca_topic_score_gemma":0.9961115,"domain_scores_codex":[0.9989892,0.00005386609,0.0003471225,0.0001204056,0.000174101,0.0003152801],"domain_scores_gemma":[0.9996973,0.00002056919,0.00004030983,0.0001660929,0.000007452395,0.00006826586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001241435,0.00001624855,0.8475065,8.80976e-7,0.0001369233,0.000002459996,0.0001057145,0.1133629,0.00001389892,0.000007916728,0.0001408497,0.03870452],"study_design_scores_gemma":[0.0002042048,0.000002055828,0.9617085,0.00001483748,0.0001699445,5.647425e-7,0.0001249934,0.03750216,0.0000431342,0.00001034272,0.00009282101,0.000126478],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971809,0.0004790797,0.001099974,0.00002833575,0.0001613964,0.00004505023,1.441676e-7,0.00004704345,0.0009581211],"genre_scores_gemma":[0.9994851,0.00005047716,0.0001062633,0.000006558769,0.00004470999,0.000008114064,0.00006702001,0.000009810448,0.0002219628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6606279,"threshold_uncertainty_score":0.6689415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088649212237954,"score_gpt":0.2365856116041729,"score_spread":0.2256991194817933,"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."}}