{"id":"W2028446460","doi":"10.5539/jmr.v4n4p46","title":"Classifying Inputs and Outputs with Fuzzy Data","year":2012,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data envelopment analysis; Mathematics; Measure (data warehouse); Fuzzy logic; Nonparametric statistics; Mathematical optimization; Linear programming; Fuzzy number; Data mining; Fuzzy set; Artificial intelligence; Computer science; Statistics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04759658,0.0001052162,0.0004118654,0.001040453,0.0002511891,0.0005238834,0.001957,0.00006555193,0.00007469604],"category_scores_gemma":[0.01271749,0.00005709022,0.00005154613,0.001387117,0.0003279894,0.001119957,0.0007756889,0.0006660831,0.0001206034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005050839,"about_ca_system_score_gemma":0.0002069099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003663261,"about_ca_topic_score_gemma":0.00001014011,"domain_scores_codex":[0.9924172,0.0005053968,0.0009366599,0.000216022,0.005443341,0.0004814364],"domain_scores_gemma":[0.9916198,0.004888888,0.0005856582,0.001161433,0.001419904,0.0003243265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005470298,0.009462943,0.3751406,0.0008908072,0.001524339,0.0007813018,0.07567828,0.000870536,0.02435453,0.08531947,0.2422337,0.1831965],"study_design_scores_gemma":[0.007797056,0.004024105,0.08216533,0.004080538,0.0009369908,0.01125834,0.08902951,0.1507328,0.009081727,0.3826266,0.2556155,0.002651492],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9384502,0.001929674,0.0459733,0.004007752,0.0001955024,0.0001512725,0.000006892047,0.00000924324,0.009276214],"genre_scores_gemma":[0.9595398,0.00005766063,0.0394741,0.00003768732,0.0002141124,5.017009e-7,4.140248e-7,0.00001313653,0.0006625737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2973071,"threshold_uncertainty_score":0.9955988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5869107755571203,"score_gpt":0.5435433094158524,"score_spread":0.04336746614126796,"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."}}