{"id":"W4395660032","doi":"10.1139/cjce-2023-0495","title":"A combined short- and medium-term traffic flow prediction method for proactive traffic control at expressway toll stations","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Toll; Traffic flow (computer networking); Term (time); Transport engineering; Computer science; Engineering; Environmental science; Computer network","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":[0.0003446861,0.0006462507,0.0004316449,0.0006835473,0.0003446049,0.0005826367,0.000867761,0.000573741,0.001052703],"category_scores_gemma":[0.0007234577,0.0002844013,0.0003975796,0.0004127657,0.0001696788,0.0009574809,0.000541271,0.0007438283,0.0002148418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004990296,"about_ca_system_score_gemma":0.0009482449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01505363,"about_ca_topic_score_gemma":0.01626529,"domain_scores_codex":[0.9997824,0.00002032091,0.00001366443,0.00007362012,0.00007045397,0.00003951559],"domain_scores_gemma":[0.9997936,0.0000373505,0.00002824057,0.00001695937,0.0001039106,0.0000199752],"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":[0.0003160868,0.0004307353,0.01748095,0.000102422,0.0001104799,0.0001539838,0.0001232189,0.5693882,0.0277147,0.001343877,0.002031612,0.3808039],"study_design_scores_gemma":[0.000006145054,0.00004046159,0.001634782,0.000003634749,0.00001545675,0.00001187249,0.00001097255,0.9964384,0.001507873,0.0001607059,0.0001609194,0.000008832394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2200685,0.0002708992,0.7734147,0.0002272541,0.0001181324,0.0001113872,0.0002539321,0.001680581,0.003854705],"genre_scores_gemma":[0.9561535,0.00007396476,0.04180494,0.00003072192,0.0000224511,0.00006715034,0.0001494571,0.00001904964,0.001678696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01505363,"threshold_uncertainty_score":0.02993202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008095776274502689,"score_gpt":0.212173457477245,"score_spread":0.2040776812027423,"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."}}