{"id":"W4200002683","doi":"10.1155/2021/9513170","title":"The Prediction of Multistep Traffic Flow Based on AST-GCN-LSTM","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Graph; Traffic flow (computer networking); Artificial neural network; Artificial intelligence; Algorithm; Real-time computing; Data mining; Computer network; Theoretical computer science","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":[0.00012534,0.00008419946,0.0001257605,0.00008774752,0.00004735051,0.00001059527,0.00007087802,0.00004185023,0.000007416425],"category_scores_gemma":[0.00001694866,0.00006915577,0.0001064128,0.0001598014,0.00001883619,0.0001744026,5.347395e-7,0.0001544763,5.867029e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003853575,"about_ca_system_score_gemma":0.00002199544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.606868e-7,"about_ca_topic_score_gemma":0.00001664294,"domain_scores_codex":[0.9991366,0.00001809163,0.0004351684,0.00006528175,0.0002562836,0.00008861799],"domain_scores_gemma":[0.9995199,0.00005653534,0.0001333096,0.0001066234,0.0001463444,0.00003727093],"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":[0.00005492847,0.00004608537,0.00004458887,0.0000438867,0.00003127258,0.00001225046,0.0001609043,0.8990817,0.003308849,0.00008022934,0.00098755,0.09614774],"study_design_scores_gemma":[0.004345081,0.0008084706,0.1458888,0.0006259617,0.0002415092,0.00001634574,0.001197351,0.7523314,0.04983374,0.0001197516,0.044316,0.0002755558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3669487,0.0007286277,0.6275306,0.0003265817,0.002478058,0.0002990975,0.00009014273,0.0008295724,0.0007685487],"genre_scores_gemma":[0.9885534,0.0007135884,0.01058799,0.00002423389,0.00005599193,0.000005491295,0.00003041139,0.00001497922,0.00001388516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6216047,"threshold_uncertainty_score":0.2820091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005727537270904096,"score_gpt":0.2066523300951531,"score_spread":0.200924792824249,"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."}}