{"id":"W2110645003","doi":"10.1287/opre.1060.0295","title":"Incorporating Multiprocess Performance Standards into the DEA Framework","year":2006,"lang":"en","type":"article","venue":"Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Efficient frontier; Computer science; Set (abstract data type); Measure (data warehouse); Dual (grammatical number); Efficiency; Sample (material); Operations research; Mathematical optimization; Econometrics; Data mining; Economics; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02228153,0.0001208791,0.0001819297,0.000554744,0.003978741,0.00212013,0.001635435,0.0001000073,0.0003818986],"category_scores_gemma":[0.01421622,0.00006983015,0.00007119154,0.005768448,0.0006945023,0.0005950648,0.0003327865,0.0007582197,0.0005931692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001951806,"about_ca_system_score_gemma":0.0008387827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001583796,"about_ca_topic_score_gemma":0.004198573,"domain_scores_codex":[0.99185,0.0008817994,0.0006783365,0.0005486778,0.005606943,0.0004342084],"domain_scores_gemma":[0.9917368,0.002501813,0.00005845591,0.001124109,0.004505492,0.00007334234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003567913,0.0002523608,0.04023591,0.00001226587,0.00001881846,0.00000993574,0.005290163,0.7950712,0.003215097,0.07149473,0.01139634,0.07296754],"study_design_scores_gemma":[0.0001685045,0.00009370255,0.008566549,0.00005149467,0.000006900977,0.000004287678,0.002784821,0.9330055,0.00378733,0.02679199,0.02452392,0.0002149677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9176379,0.0002948806,0.06521982,0.005159985,0.0001129818,0.000283693,0.00001013649,0.00003732001,0.01124329],"genre_scores_gemma":[0.9830284,0.00001133486,0.01231307,0.00009091858,0.0002408322,0.00006438467,0.000006548772,0.00001268665,0.004231845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1379344,"threshold_uncertainty_score":0.9989158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1304183218674944,"score_gpt":0.4962029636701631,"score_spread":0.3657846418026687,"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."}}