{"id":"W2058209826","doi":"10.1016/j.trc.2006.06.002","title":"Evaluation of variable speed limits to improve traffic safety","year":2006,"lang":"en","type":"article","venue":"Transportation Research Part C Emerging Technologies","topic":"Traffic and Road Safety","field":"Engineering","cited_by":269,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Crash; Speed limit; Variable (mathematics); Traffic flow (computer networking); Control variable; Reduction (mathematics); Computer science; Simulation; Transport engineering; Automotive engineering; Engineering; Mathematics; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001606586,0.0005336315,0.0005880856,0.0006177909,0.0002657198,0.0007979011,0.0009575137,0.0005888371,0.002911635],"category_scores_gemma":[0.008094346,0.0002009294,0.0002698859,0.0003883529,0.0003284706,0.000734324,0.0003246834,0.0003569126,0.0002303679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000766536,"about_ca_system_score_gemma":0.0009305594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004947941,"about_ca_topic_score_gemma":0.003232027,"domain_scores_codex":[0.9987178,0.0005583182,0.00005836746,0.0001258969,0.0004440476,0.00009555621],"domain_scores_gemma":[0.9944587,0.003673496,0.0003719754,0.0003034369,0.001040149,0.0001522328],"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":[0.01759042,0.005270561,0.04232515,0.0005279366,0.0002885128,0.0001319225,0.0003214777,0.6094057,0.05236726,0.007305151,0.001805102,0.2626609],"study_design_scores_gemma":[0.0006910017,0.01156654,0.02814612,0.00006944756,0.0004757049,0.00008491943,0.0002643776,0.8783058,0.07343034,0.00405091,0.002843761,0.00007107718],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672268,0.0004199414,0.02521014,0.0001078439,0.00005636421,0.00007114546,0.0001292277,0.0002406498,0.006537911],"genre_scores_gemma":[0.9960014,0.00005415603,0.003355235,0.00001036173,0.000004337247,0.00002077139,0.00004483733,0.00001108086,0.0004977606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004947941,"threshold_uncertainty_score":0.009838283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04762658656274438,"score_gpt":0.3227678533666299,"score_spread":0.2751412668038856,"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."}}