{"id":"W4296709144","doi":"10.1155/2022/2589681","title":"Short-Term Passenger Flow Prediction of Urban Rail Transit Based on SDS-SSA-LSTM","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Gansu Education Department; Lanzhou Jiaotong University; National Natural Science Foundation of China","keywords":"Flow (mathematics); Term (time); Decomposition; Component (thermodynamics); Computer science; Schedule; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001959439,0.000124521,0.0002003109,0.0002960712,0.00006041508,0.000006250356,0.0001119606,0.0000397017,0.00005629824],"category_scores_gemma":[0.000002982241,0.0001323554,0.0001505786,0.0002104541,0.00001487447,0.0002771369,0.000001030723,0.000283799,3.061497e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009022599,"about_ca_system_score_gemma":0.00001624619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.817155e-7,"about_ca_topic_score_gemma":0.000004272454,"domain_scores_codex":[0.9987773,0.00002648129,0.0005450681,0.00009901806,0.0004347367,0.000117392],"domain_scores_gemma":[0.9996182,0.00002360817,0.0001210224,0.0001142605,0.00006706436,0.00005581162],"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":[0.0001663281,0.0001167634,0.0006513076,0.00008239707,0.00005182287,0.00002105336,0.0006561566,0.9601127,0.01502123,0.0001070739,0.001980071,0.02103312],"study_design_scores_gemma":[0.006362141,0.003002727,0.6215802,0.0004126724,0.0005769743,0.00002463453,0.00155008,0.2866751,0.03377327,0.0001979713,0.04518578,0.0006584505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4368435,0.0001857123,0.5593093,0.000151083,0.001508655,0.0003841458,0.0002301678,0.0008426183,0.0005448457],"genre_scores_gemma":[0.9958501,0.000108086,0.003773993,0.00003598921,0.00007015641,0.00002341434,0.00009918748,0.00002777978,0.00001123859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6734376,"threshold_uncertainty_score":0.5397296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007141932448502432,"score_gpt":0.2041801032127124,"score_spread":0.19703817076421,"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."}}