{"id":"W3121244967","doi":"","title":"Urban Growth and Transportation","year":2008,"lang":"en","type":"article","venue":"ScholarlyCommons (University of Pennsylvania)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Stock (firearms); Instrumental variable; Estimation; Public transport; Population; Population growth; Business; Geography; Agricultural economics; Economics; Transport engineering; Econometrics; Engineering; Demography","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":[0.0004521348,0.0003045625,0.0003421755,0.001325002,0.0005509757,0.00126562,0.0003248323,0.0004567731,0.01220167],"category_scores_gemma":[0.00457333,0.0001967041,0.0005378131,0.00359364,0.0005982841,0.0008479042,0.001238698,0.0008938676,0.001821402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002149944,"about_ca_system_score_gemma":0.002011992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07343919,"about_ca_topic_score_gemma":0.08844982,"domain_scores_codex":[0.9993673,0.0001860764,0.0000344428,0.0001235596,0.0001520575,0.0001366525],"domain_scores_gemma":[0.9977729,0.0006764728,0.0008817393,0.0001354265,0.0003223382,0.0002110948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000470717,0.0001476808,0.8521928,0.0001234967,0.0002144677,0.0001166855,0.0005016095,0.03583187,0.0001211686,0.05598339,0.01870264,0.0360171],"study_design_scores_gemma":[0.00003645993,0.0001834278,0.7954815,0.0002205632,0.000245856,0.0001893876,0.003128452,0.04813308,0.0007777239,0.02739706,0.1241681,0.00003838151],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.835907,0.002478968,0.01762085,0.008249626,0.0001957668,0.0001735227,0.03501387,0.0003580296,0.1000025],"genre_scores_gemma":[0.9686484,0.001331872,0.001611474,0.0002217068,0.00009147933,0.0001198875,0.01017366,0.00003104756,0.01777039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07343919,"threshold_uncertainty_score":0.1460235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02196551061713624,"score_gpt":0.2289506125406306,"score_spread":0.2069851019234943,"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."}}