{"id":"W2159789307","doi":"10.3141/1854-11","title":"Empirical Investigation of Household Vehicle Type Choice Decisions","year":2003,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Discrete choice; Macro; Automotive industry; Greenhouse gas; Environmental economics; Process (computing); Work (physics); Mode choice; Simulation modeling; Nested logit; Travel behavior; Transport engineering; Computer science; Economics; Engineering; Econometrics; Microeconomics; Public transport","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004902383,0.0002526905,0.0005175413,0.001151102,0.0003812116,0.001038725,0.0007957242,0.0008785361,0.008004826],"category_scores_gemma":[0.03356165,0.0003817749,0.0005450477,0.002126681,0.0007030838,0.001670716,0.0006251137,0.00151288,0.00117151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006008621,"about_ca_system_score_gemma":0.0004288627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007618149,"about_ca_topic_score_gemma":0.006613657,"domain_scores_codex":[0.9974322,0.001676972,0.000147948,0.0002517471,0.0002690019,0.0002222353],"domain_scores_gemma":[0.9346892,0.05172692,0.008215264,0.002543217,0.001528641,0.001296805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003996086,0.000980173,0.9715864,0.00007153957,0.0002199448,0.0003011635,0.001343893,0.00554562,0.0001716229,0.00399466,0.001067231,0.01431819],"study_design_scores_gemma":[0.00004868863,0.0005071546,0.9348812,0.00005312429,0.00008179021,0.0003776182,0.005761843,0.049048,0.0004315616,0.005214633,0.003554396,0.00004000177],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974079,0.000103042,0.0008659548,0.0001519178,0.000003319901,0.00001973098,0.000553664,0.000005444562,0.000889003],"genre_scores_gemma":[0.9969837,0.0001215772,0.0004641852,0.00003736614,0.000007854239,0.0000316355,0.00112181,0.000002666308,0.001229108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008004826,"threshold_uncertainty_score":0.02677876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2336347389356914,"score_gpt":0.4423780492795777,"score_spread":0.2087433103438862,"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."}}