{"id":"W45689619","doi":"","title":"PRICING AND INVESTMENT IN A TRANSPORTATION NETWORK: THE CASE OF TORONTO AIRPORT. IN: AIR TRANSPORT","year":2002,"lang":"en","type":"article","venue":"Classics in Transport Analysis","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ministry of Transport; Transport engineering; Investment (military); Order (exchange); Christian ministry; Traffic congestion; Marginal cost; Congestion pricing; International airport; Transportation planning; Transport network; Economics; Business; Finance; Engineering; Microeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008229956,0.0001974244,0.0007817753,0.0003954339,0.00006004783,0.000005849715,0.0001390105,0.0001763781,0.0005180474],"category_scores_gemma":[0.000006235543,0.0001932882,0.0002787129,0.001989408,0.00009439795,0.0002823777,0.000002764589,0.0002572822,0.000001681594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001545329,"about_ca_system_score_gemma":0.00001243707,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01289541,"about_ca_topic_score_gemma":0.366036,"domain_scores_codex":[0.9975994,0.00002562374,0.001551803,0.0004579968,0.00006622954,0.0002989594],"domain_scores_gemma":[0.9990945,0.00005930849,0.0004309544,0.0003314028,0.00001802341,0.0000658406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009225468,0.0001689622,0.9222974,0.00002145997,0.0002388405,0.0002735154,0.00327971,0.03849123,4.485559e-7,0.03457265,0.000006712115,0.0006398818],"study_design_scores_gemma":[0.0006320499,0.00002166801,0.9567331,0.00002226957,0.0002802805,0.000003067882,0.0006176794,0.03789691,0.000003695572,0.002863436,0.0007163929,0.000209442],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886677,0.002762296,0.001645251,0.0003350291,0.00004203049,0.0001588299,0.00006637445,0.000009412555,0.006313049],"genre_scores_gemma":[0.9979966,0.00142452,0.0001563682,0.0001231942,0.00002555016,0.00004080181,0.00009431857,0.00001374294,0.0001249206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3531406,"threshold_uncertainty_score":0.9936778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03166223481589881,"score_gpt":0.2236252662169479,"score_spread":0.1919630314010491,"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."}}