{"id":"W4285595287","doi":"10.3390/make4030032","title":"Input/Output Variables Selection in Data Envelopment Analysis: A Shannon Entropy Approach","year":2022,"lang":"en","type":"article","venue":"Machine Learning and Knowledge Extraction","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal; Dalhousie University","funders":"","keywords":"Data envelopment analysis; RDM; Entropy (arrow of time); Computer science; Econometrics; Information Criteria; Data mining; Mathematical optimization; Statistics; Mathematics; Model selection; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01007107,0.0002097721,0.0004479698,0.002105413,0.001031755,0.0003278639,0.0006380025,0.00007464693,0.0004873395],"category_scores_gemma":[0.001494913,0.0001888066,0.0001005672,0.006232249,0.00004648086,0.0004271645,0.0006693709,0.0009868835,0.00004646397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002211872,"about_ca_system_score_gemma":0.0001275787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005685605,"about_ca_topic_score_gemma":0.0006106868,"domain_scores_codex":[0.9948645,0.001869384,0.0007563337,0.001174235,0.001008466,0.0003271032],"domain_scores_gemma":[0.9982483,0.0006954085,0.0004147345,0.0004334658,0.0001223389,0.00008570134],"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":[0.0001974154,0.001512789,0.3948408,0.0000189897,0.0004293305,0.00001237974,0.005209597,0.4061728,0.002738474,0.000557915,0.001982361,0.1863272],"study_design_scores_gemma":[0.0002990752,0.00005758047,0.02572747,0.000003684949,0.0001886971,0.00003103078,0.001112094,0.8535165,0.00001817587,0.0002348042,0.1186196,0.0001912216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5591637,0.005926698,0.4123866,0.001002921,0.0008585663,0.000590966,0.00004878724,0.0003800505,0.01964171],"genre_scores_gemma":[0.9880518,0.00005749339,0.00271876,0.00002473522,0.00009283536,0.00003222069,0.0002565974,0.00001525345,0.008750254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4473438,"threshold_uncertainty_score":0.7935528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.067863478137799,"score_gpt":0.3723473594554385,"score_spread":0.3044838813176395,"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."}}