{"id":"W7053383776","doi":"","title":"Wage dispersion, technology adoption and labor market polarization","year":2018,"lang":"en","type":"dissertation","venue":"Repositório Institucional da Universidade Católica Portuguesa (Universidade Católica Portuguesa)","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wage; Polarization (electrochemistry); Efficiency wage; Incentive; Productivity; Shim (computing); Technological change; Secondary labor market; Market structure; Wage growth","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":[0.0009658861,0.0001803584,0.0002740554,0.0009277827,0.0008294723,0.001677431,0.0003205402,0.0005019392,0.005719756],"category_scores_gemma":[0.004678033,0.0001399169,0.0002959111,0.001774635,0.001046326,0.000882878,0.001419155,0.0009399054,0.0004263995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009553696,"about_ca_system_score_gemma":0.0005252866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006252919,"about_ca_topic_score_gemma":0.005728978,"domain_scores_codex":[0.9993504,0.0001503727,0.00003690687,0.0001190928,0.0001599411,0.0001832693],"domain_scores_gemma":[0.9959643,0.00151817,0.001721439,0.000210014,0.0002353838,0.000350662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003394956,0.0006280179,0.7865449,0.0001977605,0.000182044,0.0005533255,0.007742283,0.01213807,0.001281838,0.09561654,0.003989949,0.09078578],"study_design_scores_gemma":[0.00004006902,0.000181275,0.8948127,0.0001810048,0.00004133924,0.0001951567,0.007767352,0.008653067,0.0004893736,0.07283108,0.01476681,0.0000407058],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974429,0.001342632,0.003126225,0.001716855,0.00002576833,0.00002799319,0.0003442533,0.00001057292,0.01897675],"genre_scores_gemma":[0.9966291,0.0007243231,0.0002955948,0.00008811388,0.00003139688,0.00001384398,0.0001607986,0.000002847795,0.002054066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006252919,"threshold_uncertainty_score":0.01913446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00718738801959145,"score_gpt":0.2063855880963004,"score_spread":0.1991982000767089,"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."}}