{"id":"W7111332813","doi":"10.1155/atr/6594630","title":"An Integrated Approach for Modeling Regional, Multicommodity, and Multimodal Freight Transport Systems","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Key Research and Development Program of China; Federal Highway Administration; Ministry of Transport of the People's Republic of China; National Natural Science Foundation of China","keywords":"Estimation; Multimodal transport; Mode (computer interface); Yangtze river; Land use; Big data; Transport network; Mathematical model; Data modeling; Statistical model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0009346615,0.001522121,0.0009506566,0.001327878,0.0005026059,0.001589054,0.001506392,0.001244187,0.00289108],"category_scores_gemma":[0.001539393,0.0008064843,0.002404509,0.001572298,0.0005217248,0.001590993,0.001490722,0.001564612,0.0003987493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001438101,"about_ca_system_score_gemma":0.001912189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02824958,"about_ca_topic_score_gemma":0.02226253,"domain_scores_codex":[0.9994796,0.000185866,0.00003712445,0.0001283198,0.0001023685,0.00006677018],"domain_scores_gemma":[0.9994598,0.0002659716,0.00007696197,0.00003684529,0.0001226051,0.00003778886],"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":[0.000004070856,0.00001421627,0.000433976,0.00002014917,0.00003320807,0.00003276052,0.00002821468,0.9848984,0.0002540775,0.009924013,0.0001768651,0.004180083],"study_design_scores_gemma":[0.000001209551,0.0000048959,0.0000616355,0.000002744453,0.000006953297,0.000003749892,0.0000088383,0.9965466,0.00003499772,0.002879619,0.0004467919,0.000002171809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01039897,0.0002339292,0.9846079,0.0001212691,0.00002785032,0.00005876211,0.0003655206,0.000234149,0.003951666],"genre_scores_gemma":[0.6032373,0.001009375,0.3880337,0.0001091644,0.000114277,0.0007326624,0.001097438,0.0001634319,0.00550257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02824958,"threshold_uncertainty_score":0.05617034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02522503831530886,"score_gpt":0.2444243124227658,"score_spread":0.219199274107457,"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."}}