{"id":"W2922073001","doi":"10.1155/2019/8618476","title":"Cross-Comparison and Calibration of Two Microscopic Traffic Simulation Models for Complex Freeway Corridors with Dedicated Lanes","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Federal Highway Administration","keywords":"Headway; Traffic flow (computer networking); Traffic simulation; Calibration; Computer science; Simulation modeling; Microscopic traffic flow model; Simulation; Microsimulation; Bottleneck; Flow (mathematics); Traffic congestion reconstruction with Kerner's three-phase theory; Traffic congestion; Transport engineering; Environmental science; Traffic generation model; Real-time computing; Engineering; Physics","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":[0.001311612,0.0009034154,0.000531422,0.0008521058,0.0003904382,0.0008653776,0.001012176,0.0008320295,0.0009161261],"category_scores_gemma":[0.003823953,0.0004521258,0.0006466188,0.0007425761,0.0004413874,0.0009883078,0.0005404034,0.0007709078,0.0001844939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001758243,"about_ca_system_score_gemma":0.001131942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03009689,"about_ca_topic_score_gemma":0.02434494,"domain_scores_codex":[0.9993736,0.000183527,0.00004542335,0.0001235158,0.0001832224,0.00009073177],"domain_scores_gemma":[0.997827,0.00077333,0.0002354986,0.000498452,0.0005672055,0.00009849422],"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":[0.00002733538,0.0000832683,0.004029152,0.000009990027,0.00001720224,0.00001567062,0.00002294751,0.9913095,0.0009592183,0.0003656161,0.0001249776,0.00303513],"study_design_scores_gemma":[0.000009744744,0.00006179465,0.002793602,0.000003857572,0.000007586211,0.000009301931,0.00002690179,0.9952797,0.00133772,0.0001887691,0.0002676114,0.00001346623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9182525,0.00005922478,0.0750378,0.0001055834,0.00005425584,0.0001686163,0.0006567281,0.0006916967,0.004973483],"genre_scores_gemma":[0.9895906,0.00003673671,0.009344344,0.00001409544,0.000003337193,0.00008223749,0.0004875615,0.00004427867,0.0003968914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03009689,"threshold_uncertainty_score":0.05984342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242851263593157,"score_gpt":0.2651004445631642,"score_spread":0.2526719319272326,"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."}}