{"id":"W4380538420","doi":"10.1155/2023/8256907","title":"Multibranch Adaptive Fusion Graph Convolutional Network for Traffic Flow Prediction","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nanyang Technological University","keywords":"Computer science; Graph; Fusion; Scale (ratio); Convolutional neural network; Spatial analysis; Artificial intelligence; Data mining; Pattern recognition (psychology); Remote sensing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005027798,0.0008920255,0.0005518466,0.0009385451,0.0003386434,0.0004729026,0.001118594,0.0006583513,0.00122809],"category_scores_gemma":[0.001293354,0.0003217643,0.0005503194,0.0008713848,0.0003741129,0.001236693,0.0007252393,0.0009912074,0.0002637717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001213216,"about_ca_system_score_gemma":0.00120836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03423803,"about_ca_topic_score_gemma":0.03831017,"domain_scores_codex":[0.9997755,0.00002748651,0.000008442327,0.00007725355,0.00005927484,0.00005205175],"domain_scores_gemma":[0.9996943,0.00008883785,0.00003365845,0.00003464527,0.0001237542,0.0000248376],"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":[0.0001768495,0.0001080038,0.004053511,0.00005004332,0.00008563399,0.00007494366,0.00004418835,0.8200967,0.006110071,0.003868531,0.004062809,0.1612687],"study_design_scores_gemma":[0.000001639269,0.000007351206,0.0002432387,0.000001548997,0.000006235147,0.000004730457,0.00000199032,0.9983565,0.0004691393,0.0007628829,0.0001422816,0.00000237128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1165257,0.001191132,0.8745055,0.0005391261,0.0001521032,0.0000639109,0.0006415825,0.002901645,0.00347935],"genre_scores_gemma":[0.9216311,0.000441563,0.0736603,0.000152445,0.00005276017,0.00005543342,0.001009733,0.00008189685,0.002914738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03423803,"threshold_uncertainty_score":0.0680775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009539013359263085,"score_gpt":0.2192657731799172,"score_spread":0.2097267598206541,"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."}}