{"id":"W4386885315","doi":"10.1016/j.tranpol.2023.09.011","title":"Does high-speed rail mitigate peak vacation car traffic to tourist city? Evidence from China","year":2023,"lang":"en","type":"article","venue":"Transport Policy","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Toll; Tourism; Business; Discrete choice; China; Transport engineering; Domestic tourism; Service (business); Mode choice; Revealed preference; Mixed logit; Preference; Advertising; Marketing; Economics; Public transport; Econometrics; Logistic regression; Geography; Microeconomics; Statistics; Mathematics; Engineering","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":[0.001135589,0.0003808799,0.0004191815,0.001175715,0.0008126531,0.001262792,0.0006480532,0.0005221925,0.003932881],"category_scores_gemma":[0.00199077,0.0001943265,0.0008129579,0.001833878,0.001164074,0.000672531,0.0007204033,0.0006115895,0.0002709611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002712441,"about_ca_system_score_gemma":0.005849972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3552588,"about_ca_topic_score_gemma":0.4160679,"domain_scores_codex":[0.9993725,0.0001310199,0.00002731116,0.00009335655,0.0001004216,0.0002753501],"domain_scores_gemma":[0.997401,0.0006061036,0.0008705672,0.000154948,0.0005460067,0.0004214407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008844074,0.0002951997,0.9647254,0.0002495991,0.0007100652,0.0007103757,0.00147243,0.002333455,0.0007523616,0.004181966,0.003824878,0.01985982],"study_design_scores_gemma":[0.00009066609,0.0002017348,0.9910034,0.0000476122,0.0005112491,0.00003007756,0.002685509,0.001099625,0.0003355495,0.0003445661,0.003633001,0.00001712169],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923756,0.0009930623,0.00005935755,0.001502013,0.00001859007,0.00001067142,0.0003142072,0.000005744384,0.00472076],"genre_scores_gemma":[0.9978291,0.0006991519,0.0000206826,0.0001438915,0.00001730098,0.0000036223,0.0002297916,0.000001713047,0.001054746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3552588,"threshold_uncertainty_score":0.7063819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04062902995148462,"score_gpt":0.2617860026456768,"score_spread":0.2211569726941921,"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."}}