{"id":"W2809923164","doi":"10.1155/2018/5942763","title":"Short-Term Origin-Destination Based Metro Flow Prediction with Probabilistic Model Selection Approach","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Scholarship Council","keywords":"Probabilistic logic; Computer science; Term (time); Inflow; Autoregressive model; Schedule; Selection (genetic algorithm); Predictive modelling; Data mining; Decision tree; Machine learning; Artificial intelligence","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":[0.000163765,0.0001383845,0.0001487799,0.0002700832,0.00005964525,0.00002216251,0.00009225651,0.00005948641,0.000003308183],"category_scores_gemma":[0.00001528978,0.0001229596,0.00005139415,0.0003148817,0.00003404545,0.0007129115,7.574401e-7,0.0001646277,5.34703e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001471992,"about_ca_system_score_gemma":0.00003131297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.648502e-7,"about_ca_topic_score_gemma":0.0000242565,"domain_scores_codex":[0.9990463,0.00001262213,0.0003808609,0.0001267507,0.0003035794,0.000129832],"domain_scores_gemma":[0.9992809,0.00001088422,0.0001091697,0.00010251,0.0004365203,0.00005996962],"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":[0.0001199916,0.00006795593,0.001057117,0.00009492273,0.00003582944,0.000001327625,0.0002168428,0.9832867,0.002600774,0.000155329,0.0003377174,0.01202552],"study_design_scores_gemma":[0.0006947437,0.000449472,0.04241727,0.00008385984,0.0001355099,0.000004877351,0.00004793461,0.9528609,0.002767045,0.0001542231,0.0002557119,0.0001284398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.205505,0.00001289712,0.7929658,0.00001221745,0.000225749,0.000224385,0.000010011,0.0007244234,0.0003195538],"genre_scores_gemma":[0.8147318,0.00001887505,0.1849872,0.000008981996,0.0001473129,0.00002268683,0.00005395945,0.00002395101,0.000005249383],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6092269,"threshold_uncertainty_score":0.5014148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119682542490998,"score_gpt":0.2269209155078407,"score_spread":0.2157240900829307,"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."}}