{"id":"W2259958760","doi":"10.5281/zenodo.1078279","title":"Ranfis : Rough Adaptive Neuro-Fuzzy Inference System","year":2007,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Rough set; Adaptive neuro fuzzy inference system; Computer science; Artificial neural network; Boundary (topology); Fuzzy logic; Soft computing; Neuro-fuzzy; Mathematics; Artificial intelligence; Algorithm; Fuzzy control system; Mathematical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005120634,0.000496328,0.0008398636,0.0006227253,0.0002543673,0.0007547778,0.0008647722,0.0006868617,0.003238299],"category_scores_gemma":[0.001092499,0.0001954634,0.0006107707,0.0004258748,0.0002702304,0.0005037894,0.0004727197,0.0007791942,0.001461491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002797385,"about_ca_system_score_gemma":0.0003838216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001771619,"about_ca_topic_score_gemma":0.001759864,"domain_scores_codex":[0.9996639,0.00008769206,0.00002511603,0.00005567385,0.0001455664,0.00002198111],"domain_scores_gemma":[0.9998243,0.00007258914,0.00002139219,0.0000221555,0.0000528137,0.000006857854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002392087,0.00006651867,0.001037824,0.0005720675,0.0002788443,0.000564293,0.00015412,0.4028086,0.02228763,0.03130091,0.009937844,0.5307521],"study_design_scores_gemma":[0.00003374867,0.0001151928,0.0006338585,0.00005109781,0.00006435684,0.0002683408,0.00002699809,0.9600196,0.005272539,0.01128728,0.02219399,0.00003302705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00530076,0.0008604442,0.986232,0.0001725567,0.0001381356,0.00006714174,0.0001424638,0.002640271,0.004446203],"genre_scores_gemma":[0.3805387,0.001393778,0.6066195,0.0002066892,0.0001659263,0.0003115353,0.0005951967,0.0001695776,0.009999041],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003238299,"threshold_uncertainty_score":0.01083314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04216527879158056,"score_gpt":0.2461308307679447,"score_spread":0.2039655519763642,"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."}}