{"id":"W3123753988","doi":"","title":"Cities and Growth: Moving to Toronto - Income Gains Associated with Large Metropolitan Labour Markets","year":2012,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Metropolitan area; Productivity; Labour economics; Matching (statistics); Benchmark (surveying); Economics; Position (finance); Earnings growth; Demographic economics; Economic growth; Geography; Finance","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003920062,0.0005387726,0.001499696,0.000946821,0.0003081863,0.0004125677,0.000779924,0.0005452052,0.000496182],"category_scores_gemma":[0.0008145436,0.0006182173,0.0002644688,0.0002322701,0.0002293042,0.0003983259,0.001534026,0.00101809,0.00003681843],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005090091,"about_ca_system_score_gemma":0.0001848916,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01114216,"about_ca_topic_score_gemma":0.02828192,"domain_scores_codex":[0.9956135,0.0001586427,0.001288606,0.001364599,0.0001231725,0.001451458],"domain_scores_gemma":[0.9972347,0.0005140546,0.0006027826,0.0009151849,0.0001564966,0.0005767993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001729567,0.0003254624,0.6439707,0.0002227883,0.00108345,0.00002365228,0.001110728,0.0005245259,0.000003998397,0.3488546,0.00008980329,0.003617307],"study_design_scores_gemma":[0.001876894,0.0002675065,0.9065353,0.0004334172,0.00004445986,0.000008768117,0.002847967,0.01291492,0.00001595308,0.05471553,0.0180997,0.002239592],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8912584,0.001644087,0.00004724759,0.0009607087,0.0002990088,0.0006207827,0.001181495,0.00003959944,0.1039487],"genre_scores_gemma":[0.984633,0.01011444,0.0004837706,0.000292076,0.0002898811,0.0002331587,0.0001311133,0.0001238968,0.003698722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2941391,"threshold_uncertainty_score":0.9996269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03406463883425324,"score_gpt":0.2773213522592178,"score_spread":0.2432567134249645,"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."}}