{"id":"W2294106464","doi":"","title":"Stochastic Data Envelopment Analysis: A Random Efficiency Perspective","year":2013,"lang":"fr","type":"article","venue":"Les Cahiers du GERAD","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; McGill University","funders":"","keywords":"Data envelopment analysis; Ranking (information retrieval); Bayesian probability; Frequentist inference; Computer science; Econometrics; Perspective (graphical); Mathematics; Statistics; Bayesian inference; Artificial intelligence","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":[0.01266409,0.001597634,0.002228808,0.004477268,0.0007028221,0.004015187,0.001651055,0.001350821,0.001946706],"category_scores_gemma":[0.03186987,0.0006789737,0.001890392,0.0047178,0.002365346,0.003796013,0.002320424,0.002675897,0.0003140383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003653841,"about_ca_system_score_gemma":0.00202286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003769822,"about_ca_topic_score_gemma":0.001764844,"domain_scores_codex":[0.989125,0.006552912,0.0005068814,0.0008372387,0.002531345,0.0004465511],"domain_scores_gemma":[0.983483,0.0129535,0.001258848,0.001028248,0.001102392,0.0001740865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000216787,0.00003267028,0.001623805,0.0001341044,0.0001065245,0.00008000474,0.0001622627,0.3487695,0.0006567659,0.6225978,0.0004648569,0.02534998],"study_design_scores_gemma":[0.000009519086,0.00004106866,0.0009667806,0.00009724684,0.0000195975,0.00004513815,0.00007952315,0.6756334,0.0008059687,0.3190612,0.003200595,0.0000400088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003996879,0.0003441499,0.9929882,0.0003079275,0.00001017038,0.00003285419,0.00005949295,0.00002676085,0.002233627],"genre_scores_gemma":[0.5190228,0.002227899,0.4753245,0.0002337952,0.000156138,0.000514044,0.0003426223,0.00009433541,0.002083806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01266409,"threshold_uncertainty_score":0.06697494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04352935928923564,"score_gpt":0.3280250220894007,"score_spread":0.2844956628001651,"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."}}