{"id":"W2903468376","doi":"10.1155/2018/5020518","title":"Real-Time Prediction of Lane-Based Queue Lengths for Signalized Intersections","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Public Security of the People's Republic of China; National Natural Science Foundation of China","keywords":"Platoon; Queue; Computer science; Kalman filter; Queueing theory; Traffic flow (computer networking); Traffic volume; Simulation; Algorithm; Real-time computing; Transport engineering; Engineering; Control (management); Artificial intelligence; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001048569,0.00006933112,0.0001517302,0.0001239537,0.00002284734,0.000003862872,0.00004606908,0.00003057867,0.00003398929],"category_scores_gemma":[0.000008396172,0.00006581893,0.0001013388,0.00008479618,0.0000173488,0.000159655,2.771565e-7,0.00004965179,0.000001083574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003349164,"about_ca_system_score_gemma":0.00001649711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006635034,"about_ca_topic_score_gemma":0.00009355188,"domain_scores_codex":[0.9993705,0.000007194363,0.0003845477,0.00005250421,0.0001055043,0.00007979857],"domain_scores_gemma":[0.9995415,0.00004290063,0.0001414399,0.00005429425,0.0001880364,0.00003183577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0006810641,0.00005436737,0.00005836312,0.0001299505,0.0001172285,0.000001838946,0.0006983755,0.7467963,0.239746,0.0001351163,0.0004173381,0.01116399],"study_design_scores_gemma":[0.0402774,0.009095945,0.5890881,0.00154109,0.002010094,0.00001642834,0.002507729,0.1599496,0.130744,0.002810556,0.0609904,0.0009687199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7253946,0.00004755803,0.2730676,0.00006015073,0.0007432266,0.0002561097,0.00006923852,0.00008809081,0.0002734037],"genre_scores_gemma":[0.991861,0.00004882412,0.00784885,0.000006254697,0.0001512141,0.00001007154,0.00003032169,0.00001372685,0.00002971113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5890297,"threshold_uncertainty_score":0.2684018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005913259480585753,"score_gpt":0.217827124497671,"score_spread":0.2119138650170852,"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."}}