{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007344686,0.0003270101,0.0006525105,0.002232724,0.001325505,0.00439026,0.0006542722,0.001548193,0.005402747],"category_scores_gemma":[0.0812236,0.0002896321,0.0002606102,0.002347987,0.001755089,0.003117461,0.002205434,0.00161856,0.0007062238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372349,"about_ca_system_score_gemma":0.0006498542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001949642,"about_ca_topic_score_gemma":0.001121017,"domain_scores_codex":[0.9948624,0.002254013,0.0004546845,0.0006485417,0.001328242,0.0004520674],"domain_scores_gemma":[0.9183869,0.05129074,0.01532881,0.007399431,0.004724194,0.002869962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002039546,0.001728024,0.8154694,0.00009553014,0.0002859501,0.0002268031,0.005730508,0.005031304,0.002218635,0.07110883,0.001971699,0.09409364],"study_design_scores_gemma":[0.00005845599,0.0004774534,0.8882943,0.00008337679,0.00007265258,0.0002590267,0.003547466,0.01075422,0.001320093,0.09276535,0.002292077,0.00007551489],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810582,0.0004735212,0.002390243,0.0009789539,0.00004002079,0.00001815374,0.00009599482,0.00002834548,0.01491655],"genre_scores_gemma":[0.9989537,0.00002332135,0.0002079932,0.00002304261,0.00001902328,0.000005895931,0.00003204176,0.000005691689,0.0007291342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007344686,"threshold_uncertainty_score":0.03884292,"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."}}