{"id":"W2074531309","doi":"10.1016/j.omega.2013.09.004","title":"Data envelopment analysis: Prior to choosing a model","year":2013,"lang":"en","type":"article","venue":"Omega","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":880,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Benchmarking; Computer science; Selection (genetic algorithm); Efficient frontier; Frontier; Production (economics); Raw data; Operations research; Production–possibility frontier; Economics; Marketing; Business; Artificial intelligence; Statistics; Mathematics; Microeconomics; Political science","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":[0.0110991,0.001060264,0.002194829,0.001883811,0.00140009,0.003524571,0.000894265,0.00150041,0.009592114],"category_scores_gemma":[0.04516249,0.001205873,0.001467636,0.002181234,0.001004889,0.005105977,0.001819775,0.005691253,0.001691943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002309573,"about_ca_system_score_gemma":0.005517525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003161523,"about_ca_topic_score_gemma":0.004800012,"domain_scores_codex":[0.9949372,0.003111759,0.0002841045,0.0003806692,0.00102572,0.0002606244],"domain_scores_gemma":[0.9771189,0.01897859,0.0007207973,0.00116205,0.001685625,0.0003340097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007094404,0.0005587375,0.005112421,0.0009076278,0.0001950488,0.0002507467,0.0009174854,0.3669988,0.00962503,0.2554692,0.006081485,0.353174],"study_design_scores_gemma":[0.00004906076,0.0002097461,0.002156614,0.0002077638,0.00005539678,0.00006405128,0.0004399035,0.8064999,0.009201315,0.1715695,0.00948324,0.0000635515],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01604694,0.0001041219,0.9785874,0.0004722158,0.00002085966,0.0002003088,0.0001334792,0.0001965555,0.00423812],"genre_scores_gemma":[0.2259924,0.000267742,0.7696226,0.0001226761,0.00005463366,0.0005536604,0.0004299882,0.0002238951,0.002732347],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0110991,"threshold_uncertainty_score":0.05869836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1825064853590864,"score_gpt":0.4111379470208777,"score_spread":0.2286314616617913,"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."}}