{"id":"W3188168891","doi":"10.3368/jhr.0617-8889r1","title":"Wages, Skills, and Skill-Biased Technical Change","year":2021,"lang":"en","type":"article","venue":"The Journal of Human Resources","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Economics; Political science; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003644753,0.000229452,0.0005490904,0.0015772,0.001557859,0.002948912,0.000479001,0.001522994,0.01742722],"category_scores_gemma":[0.03956864,0.000297193,0.0004269376,0.002430921,0.003682511,0.00168917,0.001225773,0.001598625,0.001837702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00256848,"about_ca_system_score_gemma":0.001593193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07741684,"about_ca_topic_score_gemma":0.09866572,"domain_scores_codex":[0.9986262,0.0003312609,0.00006519754,0.0002436118,0.0004497316,0.0002838701],"domain_scores_gemma":[0.9749413,0.01588279,0.003612419,0.001400632,0.00264136,0.001521568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006712887,0.0004353802,0.5405788,0.0002341327,0.0002606274,0.00040455,0.003148904,0.005772126,0.0007515381,0.1899202,0.06538908,0.1924333],"study_design_scores_gemma":[0.00005148081,0.0001118587,0.7584834,0.0002136822,0.0001024432,0.0001631677,0.002337252,0.002791144,0.0002414723,0.2132684,0.02217898,0.00005681113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6759416,0.04448139,0.004112933,0.08221792,0.0008559352,0.00006969094,0.001953773,0.00008446327,0.1902824],"genre_scores_gemma":[0.9539174,0.008549009,0.0004837166,0.001546781,0.0004063277,0.00002540902,0.0002742069,0.00003792322,0.03475918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07741684,"threshold_uncertainty_score":0.1539325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06850316248019322,"score_gpt":0.4036982408292614,"score_spread":0.3351950783490681,"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."}}