{"id":"W1507674787","doi":"10.1007/978-3-642-02282-1_10","title":"Uninorm Based Fuzzy Network for Tree Data Structures","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Connectionism; Computer science; Generalization; Fuzzy logic; Artificial intelligence; Process (computing); Simple (philosophy); Tree (set theory); Neuro-fuzzy; Theoretical computer science; Artificial neural network; Tree structure; Algorithm; Data mining; Fuzzy control system; Mathematics; Binary tree; Programming language","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":[0.001180917,0.000311791,0.0005827659,0.001240418,0.0007985735,0.001245069,0.00130729,0.0007377821,0.005097733],"category_scores_gemma":[0.002996942,0.0002425615,0.000502542,0.00111523,0.0005911134,0.002848861,0.0008806298,0.0008684993,0.0007642615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480909,"about_ca_system_score_gemma":0.001131594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0054949,"about_ca_topic_score_gemma":0.01062991,"domain_scores_codex":[0.9993547,0.00010673,0.00007195218,0.0001514266,0.0002421645,0.00007306275],"domain_scores_gemma":[0.9987091,0.0003841092,0.0001038064,0.0003136378,0.0004173484,0.00007200596],"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":[0.0007078872,0.0001853016,0.001588188,0.0002759569,0.00007160963,0.0002305141,0.0002292332,0.1756133,0.01789497,0.2590739,0.01156473,0.5325643],"study_design_scores_gemma":[0.00001452077,0.000105055,0.000407383,0.00004722319,0.00004009313,0.000141501,0.00004059159,0.8656213,0.01101923,0.1137736,0.008767015,0.00002242446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02415561,0.0002792293,0.9689691,0.0002121732,0.00007277535,0.00008783977,0.00043672,0.001365852,0.004420616],"genre_scores_gemma":[0.3538623,0.0004677649,0.6286493,0.0002036491,0.00006867513,0.000204807,0.001364828,0.0001310157,0.01504776],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0054949,"threshold_uncertainty_score":0.01705366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03068712663069595,"score_gpt":0.2494026191491987,"score_spread":0.2187154925185028,"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."}}