{"id":"W3022171003","doi":"10.1155/2020/6530530","title":"Impact of Carriage Crowding Level on Bus Dwell Time: Modelling and Analysis","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"People's Government of Jilin Province; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Dwell time; Crowding; Carriage; Schedule; Estimation; Statistics; Regression analysis; Computer science; Simulation; Transport engineering; Mathematics; Engineering; Medicine; Structural engineering; Psychology","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":[0.0002237818,0.00008177117,0.0002516667,0.0001809681,0.00009954151,0.00001673214,0.00006573496,0.00005349794,0.00004309661],"category_scores_gemma":[0.00003454072,0.00007542079,0.0001851053,0.0005998813,0.00003974549,0.0003929034,2.89287e-7,0.0001110205,6.31082e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003132757,"about_ca_system_score_gemma":0.00008851566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009540228,"about_ca_topic_score_gemma":0.00005056676,"domain_scores_codex":[0.9989915,0.00004017577,0.0004364805,0.000104255,0.0003237417,0.0001038676],"domain_scores_gemma":[0.9990234,0.00008416091,0.0004727887,0.00003699379,0.000255946,0.0001267052],"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":[0.0002264028,0.00002069551,0.02186057,0.00001051149,0.0001518991,0.000006462378,0.02205378,0.953852,0.0009224926,0.000164333,0.000007442034,0.0007234087],"study_design_scores_gemma":[0.002106752,0.0008466461,0.9480861,0.0001470864,0.0013481,7.243028e-7,0.004548073,0.04110536,0.000948107,0.0003478049,0.0001938852,0.0003213796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8658696,0.00007923895,0.1336168,0.0001573595,0.00003995786,0.00006044268,0.00005104511,0.00001164017,0.0001139639],"genre_scores_gemma":[0.9886464,0.0002025202,0.01099751,0.00002369859,0.00005645624,4.061125e-7,0.00004583178,0.000007378712,0.00001975639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9262255,"threshold_uncertainty_score":0.3075571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03551167388109531,"score_gpt":0.3128063225974652,"score_spread":0.2772946487163698,"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."}}