{"id":"W155779892","doi":"10.1007/978-3-642-35644-5_40","title":"Fuzzy Regression Models Beyond Fuzzy Rule Base Models","year":2012,"lang":"en","type":"book-chapter","venue":"Studies in fuzziness and soft computing","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Fuzzy rule; Fuzzy logic; Base (topology); Computer science; Regression analysis; Econometrics; Statistics; Artificial intelligence; Mathematics; Machine learning; Fuzzy set","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001140584,0.0008910994,0.001593066,0.0003455264,0.0005930776,0.0001789195,0.001007677,0.0004550031,0.000001570203],"category_scores_gemma":[0.00004946742,0.0007094632,0.0002326127,0.0001556352,0.0003097155,0.0007570626,0.002378444,0.0007238371,0.00001966335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001650731,"about_ca_system_score_gemma":0.00008951656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004096722,"about_ca_topic_score_gemma":0.00001656575,"domain_scores_codex":[0.9960024,0.0001078047,0.001043367,0.001252119,0.0006855371,0.0009088011],"domain_scores_gemma":[0.9973438,0.0005551021,0.0005880371,0.000943126,0.0003457435,0.0002242027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001938649,0.00003941876,0.0000686144,0.0004334994,0.0001666667,0.0001115712,0.003413787,0.005407916,0.000005056837,0.8801751,0.000956932,0.109202],"study_design_scores_gemma":[0.0008949019,0.00005884306,0.00002855515,0.001767566,0.00005402696,0.00005475483,0.000338547,0.08097145,0.00000137854,0.9139196,0.0009254332,0.000984916],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0006460217,0.1337756,0.03784886,0.0004934044,0.003442799,0.0008141591,0.00001982199,0.0004202931,0.822539],"genre_scores_gemma":[0.9604127,0.005586949,0.009950301,0.0005657416,0.00180789,0.00005426312,0.00001938107,0.0001279985,0.02147479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9597667,"threshold_uncertainty_score":0.9995356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06320386782349746,"score_gpt":0.2765456842834135,"score_spread":0.2133418164599161,"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."}}