{"id":"W2014348724","doi":"10.1080/15568310801915559","title":"The Effectiveness of Automated and Manned Traffic Enforcement","year":2009,"lang":"en","type":"article","venue":"International Journal of Sustainable Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Motor Association Foundation for Traffic Safety; Centre for Transportation Engineering and Planning","keywords":"Enforcement; Law enforcement; Deterrence theory; Computer security; Differential (mechanical device); Transport engineering; Population; Poison control; Business; Engineering; Aeronautics; Computer science; Political science; Medicine; Environmental health; Law","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004306815,0.00006712816,0.0001038524,0.00009246962,0.00003687652,0.00001798399,0.000114263,0.00003093698,0.000004427916],"category_scores_gemma":[0.00001296191,0.00004875678,0.00005052393,0.00007161795,0.00002536733,0.0001856928,9.12221e-7,0.00007547978,2.231622e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006846677,"about_ca_system_score_gemma":0.00002939566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004612921,"about_ca_topic_score_gemma":0.000002531243,"domain_scores_codex":[0.9992858,0.00002391171,0.0003198869,0.0000395179,0.0002303785,0.0001005346],"domain_scores_gemma":[0.9993963,0.0001020558,0.00009203069,0.00003460544,0.0003452386,0.00002981185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0008836204,0.00006101279,0.0006682901,0.0001255463,0.000254383,0.0001366422,0.001094143,0.9295821,0.001566092,0.04708445,0.0001103669,0.01843336],"study_design_scores_gemma":[0.002769568,0.0004206361,0.9494023,0.000209827,0.00008096734,0.00004710996,0.002966271,0.03310857,0.005326508,0.002250585,0.003241769,0.000175842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995207,0.0004431392,0.003450638,0.0001010394,0.0002248697,0.0001094527,0.000003145351,0.00005552161,0.0004051693],"genre_scores_gemma":[0.9995182,0.0003008095,0.0001021172,0.000005929201,0.00002966193,0.000001380931,0.000007826026,0.000005586246,0.00002854576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.948734,"threshold_uncertainty_score":0.1988244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002317608408485237,"score_gpt":0.2140711995338854,"score_spread":0.2117535911254001,"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."}}