{"id":"W7097225918","doi":"","title":"the source. The Changing Nature of Wage Inequality","year":2007,"lang":"en","type":"article","venue":"","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wage; Inequality; Wage inequality; Economic inequality; Production (economics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005686469,0.0006780482,0.0009362396,0.003678028,0.003796511,0.003185489,0.001373818,0.001209024,0.08363196],"category_scores_gemma":[0.004595093,0.0004770342,0.0005329903,0.008565268,0.0003743047,0.001004423,0.001397497,0.002826342,0.01233845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03091208,"about_ca_system_score_gemma":0.07767322,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9896137,"about_ca_topic_score_gemma":0.9896418,"domain_scores_codex":[0.9988528,0.00002730443,0.00004294848,0.00006994468,0.0006276274,0.000379262],"domain_scores_gemma":[0.994835,0.0001758227,0.000198225,0.000106109,0.004128138,0.0005568176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00004038261,0.000008227606,0.003358099,0.0002381887,0.00001594642,0.00007067931,0.000186684,0.00007831884,0.00004071021,0.004801272,0.9609572,0.0302042],"study_design_scores_gemma":[0.00006390995,0.000009899969,0.08040379,0.000548534,0.00003828734,0.0000887284,0.0009239612,0.0003836578,0.0002269076,0.001239653,0.9160304,0.00004222587],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.006150121,0.01568133,0.0006918787,0.05703035,0.003958457,0.0003163878,0.7228517,0.0005789284,0.1927409],"genre_scores_gemma":[0.1027334,0.02391504,0.003905075,0.005306826,0.0007926751,0.0005161701,0.1764059,0.0006790541,0.6857458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9896137,"threshold_uncertainty_score":0.2797768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01617033579734573,"score_gpt":0.2371083576531993,"score_spread":0.2209380218558536,"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."}}