{"id":"W2587199548","doi":"10.1155/2017/7396250","title":"An Empirical Framework for Intersection Optimization Based on Uniform Design","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Ministry of Education of the People's Republic of China","keywords":"VisSim; Intersection (aeronautics); Software; Computer science; Traffic simulation; Mathematical optimization; Control (management); Optimization problem; Transport engineering; Engineering; Algorithm; Mathematics","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":[0.00828751,0.001639918,0.001221899,0.002377302,0.0005411988,0.002159904,0.002208218,0.001286,0.005154515],"category_scores_gemma":[0.02174828,0.0008592138,0.001294846,0.001866943,0.002313432,0.00285589,0.002065059,0.001760383,0.0004016202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00190999,"about_ca_system_score_gemma":0.001966603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002330371,"about_ca_topic_score_gemma":0.001660248,"domain_scores_codex":[0.99463,0.002903591,0.0002003406,0.0008663141,0.001068398,0.0003313242],"domain_scores_gemma":[0.991747,0.005322338,0.001005787,0.0008206778,0.0009563567,0.0001478398],"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":[0.00003013836,0.0001047865,0.001979961,0.0001152102,0.0000442792,0.00006684205,0.00007977016,0.7349151,0.0005393524,0.2425258,0.0004440005,0.01915479],"study_design_scores_gemma":[0.00001453156,0.0001102708,0.0005000511,0.00003543417,0.00001370381,0.00002768304,0.00003928179,0.9424472,0.0002557843,0.05498144,0.001562744,0.00001183117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008503451,0.0001669646,0.9862874,0.0001090997,0.00001362009,0.00008770881,0.00004930122,0.00006672725,0.004715682],"genre_scores_gemma":[0.6043441,0.0008745497,0.3896388,0.0001122602,0.00007198155,0.001250271,0.0002330853,0.00009879829,0.003376099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00828751,"threshold_uncertainty_score":0.04382902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01706811488666987,"score_gpt":0.2823938367808833,"score_spread":0.2653257218942134,"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."}}