{"id":"W3121763229","doi":"","title":"Wages, Productivity and Aging","year":2006,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Human Resources and Skills Development Canada","keywords":"Productivity; Workforce; Wage; Economics; Labour economics; Efficiency wage; Survey data collection; Production (economics); Wage growth; Demographic economics; Mathematics; Statistics; Economic growth; Microeconomics","routes":{"ca_aff":false,"ca_fund":true,"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":[0.001589273,0.0001913713,0.0003097464,0.001351423,0.0004075755,0.001227949,0.0002749942,0.0003660872,0.005737279],"category_scores_gemma":[0.006707424,0.0001017855,0.0003606856,0.001811058,0.0004439075,0.0008797454,0.0006006812,0.0003544168,0.0007091252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005638903,"about_ca_system_score_gemma":0.0005137197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0106042,"about_ca_topic_score_gemma":0.009638644,"domain_scores_codex":[0.9995275,0.0001223178,0.00005101178,0.00009024113,0.0001097021,0.00009931534],"domain_scores_gemma":[0.9965759,0.001277113,0.001077802,0.0002519862,0.0004449252,0.0003722582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001716519,0.00007381692,0.9217855,0.0001310724,0.00009437744,0.0001728895,0.002073599,0.001308682,0.0004725695,0.006906962,0.0008407548,0.06596799],"study_design_scores_gemma":[0.000004537189,0.00008390789,0.9876655,0.00003769016,0.00003548603,0.0001349951,0.0007269809,0.0003563907,0.0001659226,0.004166847,0.006612641,0.000008933604],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734473,0.009603607,0.002111918,0.000943639,0.00007950068,0.00001858547,0.001572394,0.00001969396,0.01220341],"genre_scores_gemma":[0.9916096,0.002146349,0.00049573,0.0001042907,0.00007922887,0.00001315441,0.0005270912,0.000008076313,0.005016468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0106042,"threshold_uncertainty_score":0.02108496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0376602078181451,"score_gpt":0.2865552828476971,"score_spread":0.248895075029552,"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."}}