{"id":"W4387128507","doi":"10.1155/2023/5230483","title":"Joint Optimal Train Rescheduling and Passenger Flow Control for Speed Limit and High-Demand Scenarios of Urban Rail Transits","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Train; Solver; Limit (mathematics); Computer science; Speed limit; Mathematical optimization; Operations research; Engineering; Simulation; Transport engineering; 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":[0.0008354703,0.0009902484,0.001046073,0.0004960329,0.0005941134,0.000923973,0.00079708,0.0009358377,0.001229196],"category_scores_gemma":[0.001018195,0.0005069533,0.0006480085,0.0005046497,0.000557807,0.0006672344,0.000705455,0.0006369593,0.00007248153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001163062,"about_ca_system_score_gemma":0.001800029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02869628,"about_ca_topic_score_gemma":0.01553324,"domain_scores_codex":[0.9995771,0.0001489911,0.00001321012,0.00006419231,0.00005266014,0.0001438373],"domain_scores_gemma":[0.9996246,0.0001686719,0.00007533718,0.00001682389,0.00006085963,0.00005366722],"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":[0.00004988596,0.00002839669,0.0002464818,0.00002371807,0.000009354407,0.00005312086,0.00001498447,0.9958026,0.0004471267,0.001107996,0.0001287107,0.002087706],"study_design_scores_gemma":[0.000006834126,0.00002168451,0.0001246729,7.36682e-7,0.000003575273,0.000002925171,0.00001181872,0.9993875,0.0001019357,0.0002884059,0.00004768585,0.00000223552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5725817,0.0004112966,0.4151931,0.0003816175,0.00006239902,0.0001646404,0.0001679294,0.0005069815,0.01053042],"genre_scores_gemma":[0.9928225,0.0000592575,0.006112688,0.00001206451,0.000006881366,0.00003172185,0.00003779071,0.00001022071,0.0009069633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02869628,"threshold_uncertainty_score":0.05705845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009185786479860831,"score_gpt":0.2052153369820197,"score_spread":0.1960295505021588,"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."}}