{"id":"W189670994","doi":"","title":"Does adult training benefit Canadian workers","year":2013,"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":"","keywords":"Wage; Matching (statistics); Propensity score matching; Wage growth; Demographic economics; Economics; Psychology; Demography; Labour economics; Statistics; Mathematics; Sociology","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":[0.001365205,0.0002111952,0.0004111514,0.0008768648,0.002118941,0.001569142,0.0008469393,0.0009362182,0.01020799],"category_scores_gemma":[0.00860285,0.0001726664,0.0005059473,0.001748306,0.000577229,0.0005524921,0.0007584753,0.0008657227,0.0008105359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01940979,"about_ca_system_score_gemma":0.04216105,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.985312,"about_ca_topic_score_gemma":0.9934855,"domain_scores_codex":[0.9987028,0.00008810098,0.00002342926,0.0001214093,0.000305812,0.0007584629],"domain_scores_gemma":[0.9967003,0.0004103368,0.0005863594,0.0001611122,0.0008719095,0.001269965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006234479,0.0002080564,0.8154161,0.0002030597,0.00009409236,0.0001578268,0.002002015,0.001313394,0.0005557963,0.005162789,0.04253057,0.1317329],"study_design_scores_gemma":[0.00004612061,0.00005654972,0.9721591,0.0001422369,0.00006701301,0.00005838259,0.001692215,0.0008757478,0.0001589914,0.0006485545,0.02407552,0.00001960876],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9055293,0.004551917,0.0004852561,0.02124765,0.0002014524,0.00009240797,0.01485699,0.00004842633,0.05298652],"genre_scores_gemma":[0.9869769,0.001599155,0.0001764369,0.001490679,0.00006031939,0.0000165202,0.002005041,0.000008315771,0.007666626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01940979,"threshold_uncertainty_score":0.1408285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0419456755428233,"score_gpt":0.2738492581377604,"score_spread":0.2319035825949371,"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."}}