{"id":"W2136575324","doi":"10.1007/s40534-015-0072-4","title":"Performance-based intersection layout under a flyover for heterogeneous traffic","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Indian Institute of Technology Guwahati; Indian Institute of Technology Bombay","keywords":"Intersection (aeronautics); Queue; Microsimulation; Traffic flow (computer networking); Sensitivity (control systems); Computer science; Traffic volume; Transport engineering; Simulation; Engineering; Real-time computing; Computer network; Electronic engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001317937,0.00008616411,0.0001274958,0.0001034018,0.00001659015,0.00001391952,0.00005391975,0.00003952119,0.00000486898],"category_scores_gemma":[0.000001866112,0.00007839221,0.0001061018,0.00004151242,0.000006244206,0.0001576155,3.118359e-7,0.00006955137,0.000001462566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009129071,"about_ca_system_score_gemma":0.00002943211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001004894,"about_ca_topic_score_gemma":0.00008137574,"domain_scores_codex":[0.9993899,0.000005653118,0.0002807565,0.00005581221,0.000161612,0.0001062123],"domain_scores_gemma":[0.999706,0.0000111911,0.00007161456,0.00004905156,0.0000967214,0.00006540633],"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":[0.0002070278,0.00002972104,0.00006205097,0.00005717532,0.00005883423,0.000003102599,0.0006257856,0.9602211,0.0003189396,0.000007896461,0.0001847058,0.0382237],"study_design_scores_gemma":[0.002823604,0.0003380417,0.006336474,0.000043023,0.000126289,0.000006425829,0.0001067706,0.9883043,0.0003441094,0.00008970183,0.001366359,0.0001149252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.719378,0.0001252471,0.2798287,0.00004941136,0.0004348467,0.0001015324,0.000004448487,0.00004384959,0.0000339318],"genre_scores_gemma":[0.9990484,0.00001117364,0.0007331713,0.00003944102,0.0001079958,0.000008714898,0.00001382267,0.0000188211,0.0000184936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2796704,"threshold_uncertainty_score":0.3196742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917319393994791,"score_gpt":0.2096399389598246,"score_spread":0.1904667450198767,"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."}}