{"id":"W2001294708","doi":"10.1016/j.eswa.2009.06.091","title":"An input-oriented super-efficiency measure in stochastic data envelopment analysis: Evaluating chief executive officers of US public banks and thrifts","year":2009,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data envelopment analysis; Measure (data warehouse); Computer science; Compensation (psychology); Sensitivity (control systems); Quadratic equation; Mathematical optimization; Econometrics; Operations research; Data mining; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01400791,0.0005963239,0.0009106802,0.003607579,0.0005989467,0.002743049,0.0004897878,0.0007404277,0.00100175],"category_scores_gemma":[0.03451405,0.0002214529,0.0006121499,0.00267334,0.0007686437,0.001880616,0.0009774924,0.0005595378,0.0001610665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00211161,"about_ca_system_score_gemma":0.002826461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003876414,"about_ca_topic_score_gemma":0.004904065,"domain_scores_codex":[0.9935908,0.003739852,0.0003571082,0.0003300888,0.001593663,0.0003884378],"domain_scores_gemma":[0.9777156,0.01351863,0.002233159,0.0008126529,0.005027638,0.0006923932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001556007,0.0009697493,0.4501877,0.0003338207,0.0005672536,0.0002619252,0.001435246,0.2885857,0.00604716,0.03706663,0.003083937,0.2099048],"study_design_scores_gemma":[0.00006568526,0.001027083,0.171728,0.00007381447,0.0001526877,0.00005732778,0.001971116,0.8029637,0.008801512,0.01158985,0.001516576,0.00005269887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9410582,0.0001495062,0.05491092,0.0002085043,0.0000118421,0.00007551726,0.0001285126,0.00003632357,0.003420693],"genre_scores_gemma":[0.9899564,0.00003270599,0.009610448,0.00001940655,0.000006055253,0.00002281135,0.0001020415,0.000006885794,0.0002433009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01400791,"threshold_uncertainty_score":0.07408178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1023729515889217,"score_gpt":0.3969243716714165,"score_spread":0.2945514200824948,"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."}}