{"id":"W636627861","doi":"","title":"So You're Considering a Red Light Camera Program? Lessons and Insights from Over a Decade of Camera Operation in South and Central Ontario","year":2014,"lang":"en","type":"article","venue":"Transportation 2014: Past, Present, Future - 2014 Conference and Exhibition of the Transportation Association of Canada // Transport 2014 : Du passé vers l'avenir - 2014 Congrès et Exposition de 'Association des transports du Canada","topic":"Regulation and Compliance Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credibility; Enforcement; Legislation; Law enforcement; Red light; Computer science; Political science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003433672,0.0001946162,0.0003337417,0.001343012,0.01853688,0.006854569,0.001973389,0.001249614,0.00311437],"category_scores_gemma":[0.007820942,0.0004597685,0.0002422192,0.003813438,0.008679328,0.003249935,0.002695379,0.002513496,0.0002946951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.108458,"about_ca_system_score_gemma":0.100349,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9874147,"about_ca_topic_score_gemma":0.9959602,"domain_scores_codex":[0.9952172,0.0007875162,0.0001352309,0.0003807387,0.001573281,0.001906014],"domain_scores_gemma":[0.9884135,0.002490732,0.001441179,0.0002937116,0.003640229,0.003720755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001073685,0.0001363702,0.1405649,0.0002684376,0.00003027091,0.003058085,0.7707292,0.0004235801,0.001018677,0.01451949,0.02564222,0.04350144],"study_design_scores_gemma":[0.000007072494,0.0000405945,0.1356141,0.0002216337,0.00001599845,0.0001899347,0.7599648,0.0002130426,0.0001998514,0.0006880801,0.1027949,0.00005006837],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9177203,0.001777938,0.0004995068,0.03220019,0.00008972446,0.00008282091,0.000351317,0.00002154689,0.0472567],"genre_scores_gemma":[0.9805475,0.002316841,0.0003021514,0.002143611,0.0000269585,0.00002467771,0.0001543864,0.00004314847,0.01444055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.108458,"threshold_uncertainty_score":0.7869215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008397085952339173,"score_gpt":0.1987414314000884,"score_spread":0.1903443454477493,"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."}}