{"id":"W94444423","doi":"10.1007/978-1-4419-6142-6_9","title":"Traffic Simulation with Dynameq","year":2010,"lang":"en","type":"book-chapter","venue":"International series in management science/operations research/International series in operations research & management science","topic":"Traffic control and management","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal; Inro Consultants (Canada)","funders":"","keywords":"Computer science; Path (computing); Traffic congestion; Traffic simulation; Operations research; Calibration; Travel time; Network traffic simulation; Software; Mathematical optimization; Simulation software; Simulation; Transport engineering; Engineering; Network traffic control; Mathematics; Computer network; Microsimulation","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":[0.0008711735,0.0007071977,0.0008374243,0.0006852938,0.000773225,0.0010067,0.001465406,0.001037405,0.01552632],"category_scores_gemma":[0.002069107,0.000709453,0.0009139878,0.0008349736,0.000557448,0.001049391,0.001128322,0.001278697,0.001679313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009459562,"about_ca_system_score_gemma":0.001296383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008902267,"about_ca_topic_score_gemma":0.00516915,"domain_scores_codex":[0.9996723,0.0001308279,0.00002357421,0.0000612713,0.00006944167,0.00004258752],"domain_scores_gemma":[0.9988692,0.0006527778,0.00004734036,0.0001554951,0.0002063014,0.00006873223],"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":[0.0001283429,0.0001103146,0.00110297,0.00007968294,0.00004996427,0.00004767497,0.00005171547,0.9685211,0.0007950104,0.01344821,0.004348513,0.01131644],"study_design_scores_gemma":[0.00002171611,0.000009699836,0.00006981911,0.000004234115,0.000003967074,0.000008401155,0.000005209153,0.9956751,0.0005258744,0.001840684,0.001828933,0.000006328832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2396322,0.0007712771,0.6044366,0.001390228,0.001231784,0.0004360178,0.0125229,0.02654961,0.1130294],"genre_scores_gemma":[0.7818341,0.0003202812,0.1926339,0.0003825288,0.0001291801,0.0008277789,0.005142907,0.003051733,0.01567752],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01552632,"threshold_uncertainty_score":0.05194074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03093674975654856,"score_gpt":0.3528278560513515,"score_spread":0.3218911062948029,"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."}}