{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005719563,0.0005370441,0.0009226373,0.0002474453,0.0004649803,0.0001216537,0.0002162818,0.0003479173,0.0003024602],"category_scores_gemma":[0.00003454775,0.0005400006,0.0001980011,0.0002907438,0.0001853467,0.001276164,0.000006936378,0.0003911242,5.708282e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007396947,"about_ca_system_score_gemma":0.001396008,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7520047,"about_ca_topic_score_gemma":0.9938984,"domain_scores_codex":[0.9957798,0.000159583,0.001575305,0.0006664679,0.001255954,0.0005628575],"domain_scores_gemma":[0.9962343,0.0001957837,0.002115975,0.0002818792,0.001019761,0.000152298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003267657,0.0001472992,0.9687176,0.0004410078,0.0002937715,0.000009557359,0.01155817,0.003092558,0.001561166,0.004660566,0.008742975,0.0004485598],"study_design_scores_gemma":[0.003095571,0.00005126328,0.9664241,0.0002796359,0.000478584,8.350702e-7,0.001949031,0.0008353331,0.0008247815,0.0007617427,0.02478157,0.0005175461],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851643,0.0002121982,0.001191912,0.01087452,0.0005113986,0.0009975052,0.0006302355,0.00005374893,0.0003641658],"genre_scores_gemma":[0.9966431,0.0005509372,0.0002176483,0.0006318158,0.0002386667,0.00009974495,0.001450002,0.00004604394,0.0001220015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2418937,"threshold_uncertainty_score":0.9997051,"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."}}