{"id":"W2086415068","doi":"10.1002/atr.135","title":"Operational impacts of incident quick clearance legislation: a simulation analysis","year":2010,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislation; Incident management; Transport engineering; Computer science; Service (business); Operations research; Business; Law; Computer security; Engineering; Marketing; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003229332,0.0009509618,0.000709596,0.001440929,0.0006053336,0.001219447,0.001329377,0.001591398,0.003638778],"category_scores_gemma":[0.01005083,0.0005799345,0.001346121,0.0009951622,0.00086794,0.001034536,0.0007255462,0.00183751,0.0002482114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003424191,"about_ca_system_score_gemma":0.002149527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04189981,"about_ca_topic_score_gemma":0.01789036,"domain_scores_codex":[0.9983646,0.0008236602,0.00006341078,0.0001609145,0.0002309343,0.0003564668],"domain_scores_gemma":[0.9801293,0.01663915,0.001078984,0.0005558049,0.001277635,0.0003190989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002080914,0.0004377828,0.006096671,0.00002415174,0.0000444806,0.00005535485,0.00003478245,0.9898835,0.0003123142,0.001284776,0.00022085,0.001397153],"study_design_scores_gemma":[0.00006522656,0.0003314159,0.001871983,0.000006310623,0.00003232178,0.00001390755,0.00009411598,0.9966089,0.0003293094,0.0004760727,0.0001586862,0.00001177827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882132,0.00005052683,0.006026515,0.000191784,0.00001892141,0.0001985558,0.0004483611,0.00006215179,0.004789975],"genre_scores_gemma":[0.9969837,0.00003383433,0.00204568,0.00002431113,0.000003780059,0.00009433635,0.0001989015,0.000006149273,0.0006092021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04189981,"threshold_uncertainty_score":0.08331186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005187404396436603,"score_gpt":0.2453594007619157,"score_spread":0.2401719963654791,"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."}}