{"id":"W1996735240","doi":"10.1093/jeg/lbq016","title":"New economic geography and US metropolitan wage inequality","year":2010,"lang":"en","type":"article","venue":"Journal of Economic Geography","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Metropolitan area; Inequality; Economics; Wage inequality; Economic geography; Wage; Economic inequality; Labour economics; Geography; Mathematics","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":[0.0003434661,0.0001202912,0.0001591691,0.001311433,0.0002787146,0.0006183712,0.0001760711,0.0001335575,0.003244426],"category_scores_gemma":[0.002511088,0.00005979046,0.000141942,0.002626167,0.0005766241,0.0005856764,0.001076182,0.0003124055,0.0001823261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006828493,"about_ca_system_score_gemma":0.0002099279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02001654,"about_ca_topic_score_gemma":0.03847308,"domain_scores_codex":[0.9997912,0.00007604543,0.00001303572,0.00002671208,0.00004873248,0.00004427264],"domain_scores_gemma":[0.9988066,0.000275127,0.0005796737,0.00008585831,0.0001388497,0.0001139598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009178186,0.00006426751,0.9044937,0.00006148676,0.0001142984,0.0002727625,0.002118557,0.004940744,0.0004061685,0.05314734,0.002952163,0.03133674],"study_design_scores_gemma":[0.000008637878,0.00002716872,0.9625014,0.00005718059,0.00002749094,0.0001323364,0.001959218,0.00486454,0.0001435037,0.02208132,0.008188008,0.000009220649],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822143,0.00133882,0.00153221,0.001347832,0.00001538249,0.000004589882,0.0006027582,0.00001426906,0.01292995],"genre_scores_gemma":[0.9991803,0.0001904443,0.00010334,0.00002079032,0.000011897,0.000002763277,0.0001601101,0.000001848318,0.0003284582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02001654,"threshold_uncertainty_score":0.03980011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01476255361409305,"score_gpt":0.2217202388809976,"score_spread":0.2069576852669046,"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."}}