{"id":"W4306377086","doi":"10.3390/fi14100294","title":"A Comparative Study on Traffic Modeling Techniques for Predicting and Simulating Traffic Behavior","year":2022,"lang":"en","type":"article","venue":"Future Internet","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Traffic simulation; Traffic generation model; Network traffic simulation; Traffic flow (computer networking); Term (time); Resource (disambiguation); Domain (mathematical analysis); Simulation modeling; Transport engineering; Microsimulation; Real-time computing; Network traffic control","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004631672,0.000980208,0.0006864886,0.003562184,0.0006044183,0.001861907,0.001243273,0.001051435,0.001652303],"category_scores_gemma":[0.02190828,0.0003550038,0.001155781,0.004349544,0.0003902957,0.003715296,0.0006060809,0.001119373,0.0004618217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068873,"about_ca_system_score_gemma":0.001334627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009066323,"about_ca_topic_score_gemma":0.006520954,"domain_scores_codex":[0.9973858,0.001072305,0.0001660913,0.000338303,0.0009318301,0.0001056402],"domain_scores_gemma":[0.9794878,0.01575537,0.000553896,0.001001275,0.003012559,0.0001891369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004361273,0.0004672587,0.03703789,0.001619065,0.0004173026,0.0001447297,0.0004726106,0.3160483,0.001859907,0.03387294,0.006590865,0.601033],"study_design_scores_gemma":[0.00001774171,0.0004684825,0.01743145,0.0005512104,0.0002374922,0.0002415724,0.0005038954,0.9549679,0.001769002,0.007200965,0.01654844,0.00006180394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3510306,0.0622171,0.5219865,0.003452292,0.0009236287,0.0004487699,0.001895422,0.001715056,0.05633067],"genre_scores_gemma":[0.7879444,0.04750036,0.1582164,0.0002259823,0.0003573346,0.0002172623,0.002161322,0.0002255711,0.003151499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009066323,"threshold_uncertainty_score":0.02449489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02510900219216756,"score_gpt":0.2799512588789796,"score_spread":0.2548422566868121,"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."}}