{"id":"W1802316727","doi":"10.1002/atr.1278","title":"Optimization of headways with stop‐skipping control: a case study of bus rapid transit system","year":2014,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; Program for New Century Excellent Talents in University; National Natural Science Foundation of China; National Science Foundation","keywords":"Headway; Operating cost; Scheduling (production processes); Bus rapid transit; Transport engineering; Beijing; Computer science; Operations research; Engineering; Public transport; Operations management; Waste management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000813174,0.001050087,0.0006890213,0.0007549832,0.0008008673,0.0008761979,0.0006509189,0.001096535,0.002089543],"category_scores_gemma":[0.001047008,0.0004032597,0.001089576,0.0006875232,0.0004642303,0.0005499369,0.0005590749,0.0007977589,0.00009359432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649655,"about_ca_system_score_gemma":0.001205171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04173869,"about_ca_topic_score_gemma":0.03161337,"domain_scores_codex":[0.9994984,0.0002159289,0.00001704082,0.00005231832,0.0000827412,0.0001336531],"domain_scores_gemma":[0.999128,0.0005135848,0.0001098111,0.00003422183,0.0001362992,0.00007807976],"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":[0.0001225465,0.0001828088,0.003322706,0.0001036177,0.00004925884,0.0007039066,0.00005417904,0.9883809,0.001057824,0.001211271,0.0004039594,0.00440702],"study_design_scores_gemma":[0.00004411209,0.0002946973,0.00266229,0.000005827214,0.00004353489,0.00004856964,0.0002624704,0.9950299,0.000744168,0.0004551639,0.0003956228,0.0000136712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774745,0.0003183587,0.01415903,0.0001979122,0.00002043753,0.0001163466,0.0001826448,0.00005650943,0.00747426],"genre_scores_gemma":[0.995066,0.0001251686,0.00332498,0.000009506631,0.000005061903,0.0000370219,0.00006418222,0.000006994379,0.001361073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04173869,"threshold_uncertainty_score":0.08299148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01018527135515708,"score_gpt":0.2563698964778908,"score_spread":0.2461846251227337,"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."}}