{"id":"W2900730974","doi":"10.1109/igarss.2018.8518853","title":"Traffic Flow Prediction Based on Cascaded Artificial Neural Network","year":2018,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial neural network; Traffic flow (computer networking); Task (project management); Data mining; Real-time computing; Artificial intelligence; Flow (mathematics); Machine learning; Engineering; Computer network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004679445,0.0007221255,0.0005959319,0.001141794,0.0003739081,0.0004450656,0.0009472868,0.000551159,0.0009817273],"category_scores_gemma":[0.001091424,0.0003541975,0.0005268686,0.0006717537,0.0002018182,0.0007845523,0.0003644936,0.0006257283,0.0001642097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008406054,"about_ca_system_score_gemma":0.000661496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03247619,"about_ca_topic_score_gemma":0.02261674,"domain_scores_codex":[0.9997514,0.00002719196,0.0000141257,0.00009096659,0.00006999679,0.00004629232],"domain_scores_gemma":[0.9996217,0.0001051427,0.00004298121,0.00002552291,0.0001727797,0.00003179004],"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":[0.0002226455,0.0001965383,0.008826366,0.0000404475,0.00006428158,0.0001175836,0.00003045208,0.8673767,0.004604896,0.0006883115,0.001720877,0.1161109],"study_design_scores_gemma":[0.000001066499,0.00000773384,0.0004217417,7.598535e-7,0.000002975911,0.000002307484,9.892104e-7,0.9992185,0.000236486,0.00008002701,0.00002578825,0.000001628152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.533761,0.0007201877,0.4571764,0.0002569072,0.0003108432,0.0001104579,0.0005299492,0.001811348,0.005322909],"genre_scores_gemma":[0.9754236,0.0001638004,0.0228639,0.00002345933,0.00003820523,0.00003213922,0.0002852126,0.00001091397,0.001158649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03247619,"threshold_uncertainty_score":0.0645743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215261045755988,"score_gpt":0.2072735147908807,"score_spread":0.1951209043333208,"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."}}