{"id":"W2787295637","doi":"10.2139/ssrn.2713840","title":"Performance Measurement and Pay Dispersion","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Dispersion (optics); Business; Optics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001904358,0.00006942569,0.00009020587,0.00002201607,0.003147065,0.0001762482,0.0002506346,0.00003170415,0.00001381644],"category_scores_gemma":[0.00004249755,0.00005301507,0.00003453736,0.00001178865,0.0002358617,0.0004072399,0.00006958929,0.0004422155,0.00001752309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320176,"about_ca_system_score_gemma":0.0006175897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008352,"about_ca_topic_score_gemma":0.008684455,"domain_scores_codex":[0.9985446,0.00003270917,0.0001020367,0.0001082963,0.0002231897,0.0009891802],"domain_scores_gemma":[0.9996426,0.000004920443,0.000120368,0.0001105356,0.0000516594,0.00006988402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005365313,0.0000820053,0.6602727,0.000004272328,0.00009848915,0.000002030398,0.006526135,0.000001060616,0.002250694,0.1267212,0.0001668961,0.2038209],"study_design_scores_gemma":[0.005420441,0.002231807,0.5306751,0.000271677,0.0002532379,0.0002008051,0.1535866,0.0001660711,0.004003659,0.2208157,0.08036923,0.002005611],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981805,0.001713074,0.00001288736,0.002742308,0.0002657138,0.00007432773,2.769316e-7,0.0000107389,0.01337569],"genre_scores_gemma":[0.9774092,0.02120681,0.00002061017,0.00002024162,0.0001867951,0.0000028288,8.604285e-8,0.000005812612,0.001147599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2018152,"threshold_uncertainty_score":0.9981507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03467866594128467,"score_gpt":0.3086646041330596,"score_spread":0.2739859381917749,"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."}}