{"id":"W2606830439","doi":"10.1016/j.measurement.2017.04.028","title":"Review of efficiency ranking methods in data envelopment analysis","year":2017,"lang":"en","type":"article","venue":"Measurement","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":154,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Data envelopment analysis; Ranking (information retrieval); Computer science; Data mining; Process (computing); Machine learning; Statistics; Mathematics","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":[0.02719523,0.002270347,0.00469551,0.01365003,0.0008398884,0.00555032,0.002908924,0.001614846,0.003480115],"category_scores_gemma":[0.05623991,0.001096443,0.002946342,0.02972293,0.001573478,0.004913023,0.001680581,0.002799609,0.001241171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003994611,"about_ca_system_score_gemma":0.005853592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003764902,"about_ca_topic_score_gemma":0.004193912,"domain_scores_codex":[0.9784153,0.009231541,0.003480777,0.001627209,0.00687201,0.0003732406],"domain_scores_gemma":[0.9371242,0.04752238,0.002902128,0.001767256,0.01041259,0.0002714162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006329871,0.00006720849,0.0007260057,0.03173659,0.0007288305,0.00003697223,0.0001081394,0.005924501,0.0004641758,0.05426666,0.01725537,0.8886222],"study_design_scores_gemma":[0.00007332547,0.0003574985,0.00897889,0.05101361,0.002806922,0.0007188121,0.0006436696,0.03705763,0.004196188,0.1321449,0.7616534,0.0003551445],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008095638,0.9254893,0.06707571,0.001817855,0.0005599936,0.00006134097,0.0002500179,0.00006400132,0.003872246],"genre_scores_gemma":[0.02335106,0.9007971,0.07185471,0.0008312787,0.001409521,0.0002039822,0.0004833356,0.00009731905,0.0009716085],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02719523,"threshold_uncertainty_score":0.1438239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5498016735291982,"score_gpt":0.5494259526118173,"score_spread":0.0003757209173809173,"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."}}