{"id":"W4415212874","doi":"10.1155/atr/5983189","title":"Analysis of Traffic Congestion Factors in Typical Sections of Expressways Using Structural Equation Model","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Beijing Municipal Natural Science Foundation; Beijing Municipal Education Commission; National Natural Science Foundation of China","keywords":"Smoothness; Traffic congestion; Traffic congestion reconstruction with Kerner's three-phase theory; Traffic flow (computer networking); Field survey; Variable (mathematics); Structural equation modeling; Control (management)","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":[0.002307327,0.0008377171,0.0006742101,0.003043892,0.0006557322,0.001156313,0.001134831,0.0008475452,0.002630085],"category_scores_gemma":[0.007118833,0.0005403133,0.002655323,0.003121406,0.0005583189,0.001478696,0.001355861,0.001295663,0.0002756704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001747623,"about_ca_system_score_gemma":0.002147916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04012824,"about_ca_topic_score_gemma":0.02396672,"domain_scores_codex":[0.997965,0.0007723527,0.000157315,0.0003976579,0.0004212626,0.0002865087],"domain_scores_gemma":[0.9955221,0.002474817,0.000760569,0.0001949509,0.000819028,0.0002284972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008886384,0.000422465,0.9187121,0.00007650816,0.0004508148,0.0002287746,0.001232269,0.06475072,0.0006470283,0.003346375,0.0007135968,0.009330364],"study_design_scores_gemma":[0.00003377407,0.0002975285,0.4050986,0.00007310836,0.0003715223,0.0001011542,0.002434174,0.5871006,0.000422527,0.002734859,0.00126672,0.00006526708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985643,0.00009503073,0.01225504,0.0002070016,0.00001433193,0.0001108715,0.0005289673,0.00006212566,0.001083722],"genre_scores_gemma":[0.9960654,0.00007221712,0.002536352,0.00001406368,0.00000628993,0.0001117915,0.0008378752,0.000006091424,0.0003498978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04012824,"threshold_uncertainty_score":0.07978934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01683111334294978,"score_gpt":0.2678411865506991,"score_spread":0.2510100732077493,"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."}}