{"id":"W2990948846","doi":"10.1080/21681015.2019.1692917","title":"A unique mathematical programming algorithm for performance optimization of organizational indicators in manufacturing sector","year":2019,"lang":"en","type":"article","venue":"Journal of Industrial and Production Engineering","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Data envelopment analysis; Computer science; Algorithm; Fuzzy logic; Production (economics); Investment (military); Set (abstract data type); Fuzzy set; Mathematical optimization; Data mining; Mathematics; Artificial intelligence; Economics","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":[0.002494736,0.00007837015,0.0002585514,0.001008907,0.00002913115,0.00004438976,0.0001326477,0.00008259671,0.00004474246],"category_scores_gemma":[0.001496981,0.00005988557,0.00004843613,0.001032534,0.00001869464,0.0003310966,0.0000200794,0.0001882816,7.053137e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004210894,"about_ca_system_score_gemma":0.00007118436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.254183e-7,"about_ca_topic_score_gemma":9.120748e-8,"domain_scores_codex":[0.9985023,0.00003360165,0.0007549914,0.0001423503,0.0004619754,0.000104843],"domain_scores_gemma":[0.9989524,0.0002206308,0.0004667975,0.0000924365,0.0002280218,0.00003966653],"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":[0.00002371412,0.00004168325,0.004657972,0.00002350374,0.00001898705,3.980769e-7,0.0002315496,0.9368162,0.0005380099,0.00006916499,0.00001282939,0.05756598],"study_design_scores_gemma":[0.001223623,0.0003376139,0.001342923,0.0003954252,0.00004322479,0.0001085439,0.0003570949,0.9407394,0.05381793,0.0003490122,0.001073447,0.0002117625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8241157,0.00002702209,0.1750517,0.0001659264,0.0004442087,0.0001791583,0.000001049989,0.000005542858,0.000009707667],"genre_scores_gemma":[0.9448865,0.00001060185,0.05469546,0.000002676169,0.0003429338,0.000001901158,0.000001109997,0.000008987743,0.0000498181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1207708,"threshold_uncertainty_score":0.2442063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03439160280356902,"score_gpt":0.2737893372316187,"score_spread":0.2393977344280497,"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."}}