{"id":"W2952089901","doi":"10.1080/03155986.2019.1624489","title":"DEA-based production planning considering production stability","year":2019,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Anhui Province; National Natural Science Foundation of China","keywords":"Data envelopment analysis; Production (economics); Stability (learning theory); Production planning; Computer science; Operations research; Scale (ratio); Mathematical optimization; Industrial engineering; Mathematics; Engineering; Economics; Machine learning; Microeconomics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001995044,0.001131248,0.001316439,0.00109128,0.0007404326,0.002083221,0.0008953468,0.0008631863,0.001642853],"category_scores_gemma":[0.004172576,0.000657979,0.0008065869,0.001614741,0.0007367294,0.001344399,0.001212356,0.001026895,0.0002436832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001815214,"about_ca_system_score_gemma":0.00199787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009744489,"about_ca_topic_score_gemma":0.006216014,"domain_scores_codex":[0.998943,0.0004128402,0.00007493562,0.0002069946,0.0002509075,0.0001113449],"domain_scores_gemma":[0.9984241,0.0009727117,0.0001952695,0.00007824157,0.0002807251,0.0000489684],"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":[0.000009767728,0.000006527144,0.0001579787,0.00001834487,0.00001071804,0.00002128582,0.00001571618,0.9900779,0.0002691362,0.004119599,0.00008088264,0.005212071],"study_design_scores_gemma":[0.000002067979,0.000007440319,0.00004897478,0.000003642978,0.000003622309,0.000005457962,0.000008556015,0.9966286,0.0001958801,0.002879982,0.0002129186,0.00000284445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.012416,0.0002107996,0.9836735,0.0001018158,0.00001657904,0.00006693345,0.00007701488,0.00007562612,0.003361646],"genre_scores_gemma":[0.8397755,0.0005210804,0.1563529,0.00004947219,0.00002785006,0.0003065761,0.0002371676,0.00005449176,0.002675021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009744489,"threshold_uncertainty_score":0.01937556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.243521601865345,"score_gpt":0.4472839929479381,"score_spread":0.203762391082593,"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."}}