{"id":"W4401405999","doi":"10.33423/jabe.v26i3.7147","title":"Using Data Envelopment Analysis to Analyze Academic Programs in a Business College","year":2024,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data envelopment analysis; Set (abstract data type); Computer science; Efficiency; Data set; Operations research; Mathematical optimization; Statistics; Mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005885581,0.0002323483,0.0009582965,0.003317667,0.0001137274,0.0007229592,0.001347972,0.0001387465,0.00004138536],"category_scores_gemma":[0.0003206052,0.0001783297,0.0001215626,0.01078145,0.00009552706,0.0007969643,0.0005374044,0.0003077534,0.00002152925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002113848,"about_ca_system_score_gemma":0.000546409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007554571,"about_ca_topic_score_gemma":0.0003682575,"domain_scores_codex":[0.996478,0.00003913978,0.001905673,0.0007195832,0.0005220144,0.0003356173],"domain_scores_gemma":[0.997793,0.0003310751,0.0006041744,0.0006611716,0.0004229222,0.0001876307],"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":[0.0003643805,0.0002535419,0.0252755,0.00006509719,0.001509531,0.0001631635,0.00170704,0.7748618,0.0008633644,0.005097355,0.0009025709,0.1889367],"study_design_scores_gemma":[0.0008229302,0.00003384253,0.1214326,0.0002363335,0.001832776,0.0001457345,0.002794851,0.8030908,0.00006307026,0.009872626,0.05884761,0.0008268629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750093,0.000510284,0.02188232,0.001786145,0.0003641804,0.0001592439,0.00003294861,0.00001039415,0.0002452045],"genre_scores_gemma":[0.9892755,0.0005232271,0.009750576,0.0001710111,0.0002065527,0.000002648241,0.00001136575,0.00001844643,0.00004069246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1881098,"threshold_uncertainty_score":0.7272072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1761912693870671,"score_gpt":0.3727261949939591,"score_spread":0.196534925606892,"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."}}