{"id":"W2735644255","doi":"10.1080/17457300.2017.1341935","title":"Intervention analysis of the safety effects of a legislation targeting excessive speeding in Canada","year":2017,"lang":"en","type":"article","venue":"International Journal of Injury Control and Safety Promotion","topic":"Traffic and Road Safety","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Legislation; Legislature; License; Poison control; Intervention (counseling); Transport engineering; Occupational safety and health; Collision; Enforcement; Engineering; Environmental health; Sanctions; Law enforcement; Injury prevention; Human factors and ergonomics; Computer security; Medicine; Law; Computer science; Political 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":[0.002646158,0.0005647428,0.0007835239,0.001064078,0.002933395,0.0007263446,0.001599829,0.0007049913,0.001912702],"category_scores_gemma":[0.007949117,0.0003320767,0.0008630604,0.002113284,0.001214756,0.0002558412,0.001052097,0.001099332,0.0001298269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06315438,"about_ca_system_score_gemma":0.1284995,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9848021,"about_ca_topic_score_gemma":0.9905501,"domain_scores_codex":[0.994049,0.001841771,0.0002039877,0.0005292871,0.001332378,0.002043606],"domain_scores_gemma":[0.9945108,0.0008474989,0.0009424834,0.0002560696,0.002441177,0.001002009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01622811,0.01901486,0.7019485,0.001971458,0.001644565,0.0009701047,0.01034966,0.01190197,0.01064955,0.004021563,0.008736473,0.2125631],"study_design_scores_gemma":[0.0005623583,0.006156762,0.9796464,0.00008339386,0.0005091123,0.00003083346,0.003494344,0.002584684,0.00169681,0.0001632578,0.005022538,0.00004966556],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944181,0.0002829353,0.0006069533,0.0003124741,0.00002276244,0.001156352,0.0009131377,0.00002928528,0.002258027],"genre_scores_gemma":[0.9946984,0.0002501258,0.001354579,0.0002005176,0.000008468216,0.0006496443,0.0006403964,0.000004570413,0.002193379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06315438,"threshold_uncertainty_score":0.4582192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003518323401074793,"score_gpt":0.2195869239825468,"score_spread":0.216068600581472,"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."}}