{"id":"W2051546561","doi":"10.1080/00085030.2009.10757610","title":"Alcohol and Driving: The Development of Law Enforcement Countermeasures in Canada","year":2009,"lang":"en","type":"article","venue":"Canadian Society of Forensic Science Journal","topic":"Alcohol Consumption and Health Effects","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislation; Driving under the influence; Law enforcement; Parliament; Legislature; Drunk driving; Enforcement; Test (biology); Law; Engineering; Political science; Business; Computer security; Criminology; Poison control; Psychology; Environmental health; Human factors and ergonomics; Medicine; Computer science; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001165885,0.00006766724,0.0001655379,0.00006656432,0.0003299807,0.00001579582,0.0001262103,0.00002446398,0.00003003137],"category_scores_gemma":[0.00004072193,0.00004787445,0.00003586598,0.0002002382,0.0004872596,0.00007231309,0.000009305848,0.0001909763,2.117442e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001402077,"about_ca_system_score_gemma":0.01782025,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6426155,"about_ca_topic_score_gemma":0.9805994,"domain_scores_codex":[0.9987208,0.00001017024,0.000315854,0.00009702642,0.0005301223,0.0003260207],"domain_scores_gemma":[0.9990883,0.00002713488,0.0001276978,0.0000999414,0.0001786303,0.00047825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006165728,0.00005874885,0.6419409,0.0002254414,0.00009954214,0.00004709136,0.03827425,0.0001021445,0.01191635,0.00860919,0.0226736,0.2759911],"study_design_scores_gemma":[0.0007937011,0.00008239229,0.9840386,0.0003294674,0.00001257516,0.0001458879,0.002817662,0.0006550943,0.004262134,0.0001036662,0.006679313,0.00007949966],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994625,0.0002029232,0.00001950419,0.003043103,0.000109934,0.0001589233,9.214735e-7,0.000001156851,0.001838553],"genre_scores_gemma":[0.9934065,0.0000391151,0.002250533,0.004263235,0.00002169082,8.235088e-7,3.657989e-7,0.000002083758,0.00001566391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3420977,"threshold_uncertainty_score":0.9877478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06111233564083843,"score_gpt":0.3280816372744492,"score_spread":0.2669693016336108,"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."}}