{"id":"W4383709720","doi":"10.1016/j.tra.2023.103733","title":"Metropolitan area heterogeneity and the impact of road infrastructure improvements on VMT","year":2023,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Metropolitan area; Vehicle miles of travel; Quantile regression; Stock (firearms); Econometrics; Elasticity (physics); Quantile; TRIPS architecture; Geography; Economics; Transport engineering; 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":[0.001720184,0.000182643,0.0003460145,0.0007202482,0.0002404115,0.0008636921,0.0006152144,0.0003953805,0.004329795],"category_scores_gemma":[0.01253526,0.0001889848,0.0007590551,0.001269195,0.0006904714,0.0007767651,0.001186369,0.000847779,0.0002466203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001405718,"about_ca_system_score_gemma":0.0005596501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02088423,"about_ca_topic_score_gemma":0.01804523,"domain_scores_codex":[0.9984095,0.0006280465,0.00008225138,0.0002280476,0.0002204428,0.000431853],"domain_scores_gemma":[0.9905036,0.003745148,0.003661747,0.0008806381,0.0006651336,0.0005438108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003331169,0.0002506458,0.8281029,0.00008614273,0.0007919355,0.0005071893,0.0003399361,0.1404472,0.001454663,0.01004064,0.001319776,0.01632584],"study_design_scores_gemma":[0.00002428892,0.0001607248,0.9559517,0.00002621184,0.000131326,0.0001182471,0.0008187201,0.03541222,0.0007460769,0.004591408,0.001991356,0.00002789126],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922611,0.0002427744,0.002682778,0.0005034073,0.00001262929,0.00002615565,0.000652615,0.00004520834,0.003573153],"genre_scores_gemma":[0.9993625,0.00003239048,0.0001278962,0.00002537692,0.000006237193,0.000004988256,0.0001564416,0.000003871842,0.000280262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02088423,"threshold_uncertainty_score":0.0415253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2156623013761903,"score_gpt":0.4026244839984823,"score_spread":0.1869621826222921,"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."}}