{"id":"W4324123232","doi":"10.35741/issn.0258-2724.58.1.37","title":"A MULTI-OBJECTIVE OPTIMIZATION FRAMEWORK FOR TRAFFIC SIGNAL DESIGN","year":2023,"lang":"en","type":"article","venue":"Journal of Southwest Jiaotong University","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Phaser; Queue; Intersection (aeronautics); Plan (archaeology); Software; Computer science; Index (typography); Sequence (biology); Transport engineering; Operations research; Simulation; Real-time computing; Engineering; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000246178,0.0001051205,0.0001765663,0.0002812558,0.00009351951,0.00002169034,0.0001584912,0.00007698181,0.00001929514],"category_scores_gemma":[0.00002777754,0.0001092528,0.0001396825,0.0003335877,0.00002101367,0.0001720682,0.00001764146,0.000157716,0.00001003895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001286691,"about_ca_system_score_gemma":0.00003539233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002051613,"about_ca_topic_score_gemma":0.000005018218,"domain_scores_codex":[0.9994244,0.00002991164,0.0001527099,0.00008692937,0.0001245922,0.0001814534],"domain_scores_gemma":[0.9994734,0.000173469,0.00008896784,0.00006941335,0.0001134968,0.00008123916],"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":[0.0001092915,0.00002883806,0.00003051087,0.00002363813,0.0001404742,0.00004831511,0.001034646,0.995679,0.00007774893,0.0001288534,0.000432034,0.002266622],"study_design_scores_gemma":[0.002169607,0.0001795312,0.00401951,0.0000757656,0.0001682227,0.000006756868,0.003560876,0.987794,0.00004046973,0.00007964588,0.001713161,0.0001924157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03980802,0.00003096464,0.959269,0.00006310677,0.0003215193,0.0002547837,0.0000150225,0.0001925908,0.00004492658],"genre_scores_gemma":[0.8798093,0.00006321348,0.1198355,0.000009675385,0.0001097579,9.368339e-7,0.000003526365,0.00001962632,0.0001485145],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8400012,"threshold_uncertainty_score":0.4455201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0186104445741323,"score_gpt":0.2081167819619784,"score_spread":0.1895063373878461,"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."}}