{"id":"W2890826880","doi":"10.1016/j.ejor.2018.09.008","title":"A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution","year":2018,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Measure (data warehouse); Computer science; Endowment; Econometrics; Operations research; Mathematical optimization; Economics; Mathematics; Data mining","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03860837,0.0001478374,0.0003136697,0.002212056,0.0007088333,0.0006025014,0.001673085,0.0000486327,0.0001183292],"category_scores_gemma":[0.0085004,0.00009165849,0.00008451506,0.003880922,0.0008877964,0.0006976342,0.000448838,0.0005338056,0.0001125798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002138156,"about_ca_system_score_gemma":0.0008966599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003849602,"about_ca_topic_score_gemma":0.0001551478,"domain_scores_codex":[0.9920397,0.002513056,0.0009216097,0.0006132365,0.003614196,0.0002982292],"domain_scores_gemma":[0.9925619,0.0008887824,0.0003269996,0.0008464141,0.005197351,0.0001785052],"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":[0.0008115078,0.0009799005,0.02639122,0.000007659633,0.0005505969,0.0001406699,0.001114094,0.9098164,0.0101587,0.002657946,0.0017778,0.04559347],"study_design_scores_gemma":[0.0005934201,0.0002616895,0.05156635,0.00002837181,0.00006740624,0.00001181416,0.0002194817,0.9457633,0.00007695091,0.0001096726,0.001193493,0.0001080054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2694595,0.0002403509,0.72807,0.001253671,0.00002139147,0.0001147443,0.00002219711,0.00001091979,0.0008072309],"genre_scores_gemma":[0.9448441,0.000009749779,0.0541505,0.00003165533,0.0000459023,0.000001014627,0.0000206132,0.00001276916,0.0008837176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6753846,"threshold_uncertainty_score":0.9998514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5396066245187701,"score_gpt":0.5337896822506221,"score_spread":0.005816942268147995,"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."}}