{"id":"W2498600357","doi":"10.1016/j.aap.2016.07.005","title":"Vehicle impoundments improve drinking and driving licence suspension outcomes: Large-scale evidence from Ontario","year":2016,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"Ministère des Transports","keywords":"Recidivism; Engineering; Poison control; Population; Drunk drivers; Human factors and ergonomics; Transport engineering; Injury prevention; Environmental health; Drunk driving; Psychology; Criminology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003964825,0.0002606426,0.0005897517,0.0002655546,0.0001722822,0.00007692118,0.0001343488,0.0001038633,0.001189127],"category_scores_gemma":[0.0001089869,0.00017335,0.0004371373,0.0003917562,0.00003106871,0.0009206866,0.0001362802,0.0001144197,0.00008525481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004941378,"about_ca_system_score_gemma":0.00006030183,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002698641,"about_ca_topic_score_gemma":0.5657866,"domain_scores_codex":[0.9979163,0.00007805316,0.0005014191,0.0006297709,0.0005085143,0.0003658938],"domain_scores_gemma":[0.9985989,0.0002954052,0.0002846944,0.0005624217,0.0001052412,0.0001532855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007151353,0.0001187242,0.9732072,5.82245e-7,0.001152232,0.00002003556,0.001656038,7.832834e-7,0.01951065,0.000004804368,0.00002583578,0.004231539],"study_design_scores_gemma":[0.002186656,0.00009440881,0.9856473,0.0005186325,0.004247908,0.000001708049,0.000465534,0.0001232876,0.006167518,0.0003212584,0.0000262099,0.0001995355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953339,0.0004416501,0.003128058,0.0004703841,0.0001383928,0.0003665722,6.579621e-8,0.00007759821,0.00004344687],"genre_scores_gemma":[0.9922794,0.0004233719,0.001147683,0.0001073871,0.00006248464,0.00002992936,0.00003728684,0.00001896866,0.00589351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5630879,"threshold_uncertainty_score":0.9997239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02102113537694764,"score_gpt":0.2972710391995783,"score_spread":0.2762499038226306,"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."}}