{"id":"W2129025153","doi":"10.3141/2193-10","title":"Modeling Private Car Ownership in China","year":2010,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Center for the Environment, Harvard University; V. Kann Rasmussen Foundation; Brown University","keywords":"Megacity; Car ownership; Urbanization; Beijing; China; Business; Population; Socioeconomic status; Geography; Economic growth; Demographic economics; Socioeconomics; Public transport; Economics; Transport engineering; Economy; Environmental health","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":[0.001947469,0.0009920573,0.0009696152,0.00159316,0.0006722778,0.001693826,0.002434229,0.0009385393,0.002987852],"category_scores_gemma":[0.003748452,0.0006676214,0.001168532,0.001974197,0.0009330537,0.00132045,0.001458674,0.0005589163,0.0002993131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005423851,"about_ca_system_score_gemma":0.003960853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3980032,"about_ca_topic_score_gemma":0.1995532,"domain_scores_codex":[0.9993505,0.0001572656,0.00002582146,0.0001763673,0.00007755193,0.000212413],"domain_scores_gemma":[0.9982544,0.0008196862,0.000263846,0.000135022,0.0003041472,0.0002229481],"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":[0.0001002771,0.0001265712,0.1472196,0.00003836162,0.0001154773,0.000372553,0.0002706324,0.8362801,0.0003077017,0.004809488,0.0008046373,0.00955449],"study_design_scores_gemma":[0.00001111356,0.00002051192,0.01252941,0.000004661946,0.00002109422,0.00001285228,0.00006571605,0.9860512,0.00006459327,0.0008890037,0.0003202648,0.000009514006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916859,0.0001871134,0.005435109,0.0002347075,0.000009914091,0.00005064325,0.0008508203,0.00005900227,0.001486671],"genre_scores_gemma":[0.9959249,0.0001439827,0.001169874,0.00001645855,0.000004628171,0.00004747041,0.0005507697,0.00001385263,0.002128041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3980032,"threshold_uncertainty_score":0.7913731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.107124963322821,"score_gpt":0.4163839171469988,"score_spread":0.3092589538241779,"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."}}