{"id":"W4412977190","doi":"10.1007/s40815-025-02082-1","title":"A Type-3 Fuzzy Logic System with Uncertainty Bound Type-Reduction and Optimized Secondary Memberships and Level of Alpha-Cuts","year":2025,"lang":"en","type":"article","venue":"International Journal of Fuzzy Systems","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Sakarya Üniversitesi","keywords":"Alpha (finance); Type (biology); Computational intelligence; Fuzzy logic; Reduction (mathematics); Mathematics; Computer science; Artificial intelligence; Statistics; Geometry","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":[0.0009846864,0.0001938425,0.000531523,0.0003585042,0.00007860722,0.0002841295,0.000649597,0.0001082397,0.000001501402],"category_scores_gemma":[0.00007319668,0.0001395713,0.00007252725,0.0002892427,0.0001136424,0.0004723171,0.0001193727,0.0002218097,0.000002261365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000191377,"about_ca_system_score_gemma":0.0004013963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004188673,"about_ca_topic_score_gemma":0.00001762,"domain_scores_codex":[0.9979246,0.0002258402,0.0007838914,0.0002724198,0.0006129061,0.000180328],"domain_scores_gemma":[0.997311,0.0001644753,0.0007720489,0.0002222202,0.001421702,0.0001085609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004131916,0.000345155,0.003670149,0.001584308,0.004607097,0.0006088853,0.002996051,0.01836341,0.009191092,0.9281119,0.006919206,0.01947081],"study_design_scores_gemma":[0.1315393,0.01986893,0.05956646,0.05037115,0.002898751,0.1387934,0.07564643,0.3406638,0.004476912,0.1204644,0.04746987,0.008240635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5945444,0.04610218,0.1643746,0.007675724,0.0431533,0.002444508,0.0001250993,0.0002780874,0.141302],"genre_scores_gemma":[0.9972544,0.0000894547,0.001549429,0.00005610821,0.0002835211,0.000006009119,0.000002259919,0.000008018929,0.0007507929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8076475,"threshold_uncertainty_score":0.5691552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03583585105666871,"score_gpt":0.2676144506674983,"score_spread":0.2317785996108296,"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."}}