{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0003093493,0.001474934,0.001251432,0.00250805,0.001031893,0.0002396273,0.001221614,0.002217732,0.0009584],"category_scores_gemma":[0.00009146358,0.0018014,0.0004302023,0.002650138,0.0006329761,0.001358461,0.0002694663,0.001527234,0.0001696084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136973,"about_ca_system_score_gemma":0.0007394045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001868184,"about_ca_topic_score_gemma":0.0003189513,"domain_scores_codex":[0.9945071,0.0001035152,0.001150844,0.001924449,0.001088103,0.001226037],"domain_scores_gemma":[0.9956251,0.000106673,0.0007858169,0.001628365,0.0008848844,0.0009691871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001774216,0.001699724,0.005808562,0.003432776,0.004861267,0.004007128,0.006509708,0.0004178985,0.2845113,0.1691269,0.4690646,0.04878591],"study_design_scores_gemma":[0.003397526,0.0005173062,0.0479117,0.001530791,0.002349487,0.001046828,0.00858608,0.003069217,0.01088845,0.001091576,0.914377,0.005234021],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8188369,0.005638985,0.001078169,0.003659629,0.003195856,0.00375369,0.002522707,0.004641891,0.1566721],"genre_scores_gemma":[0.8870498,0.005762547,0.004122773,0.0003481675,0.0009678621,0.0001411299,0.02366031,0.0005879943,0.07735939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4453124,"threshold_uncertainty_score":0.9999549,"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."}}