{"id":"W2513568912","doi":"10.20533/iji.1742.4712.2010.0029","title":"A Biologically-Inspired Type-2 Fuzzy Set Based Algorithm for Detecting Misbehaving Nodes in Ad-Hoc","year":2010,"lang":"en","type":"article","venue":"International Journal for Infonomics","topic":"Artificial Immune Systems Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Set (abstract data type); Fuzzy logic; Algorithm; Artificial intelligence; Type (biology); Pattern recognition (psychology); Data mining; Biology","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":[0.0004170544,0.0001288287,0.0001526738,0.0001978296,0.0001081683,0.0001389686,0.0003738949,0.0001229905,0.00001466464],"category_scores_gemma":[0.0001880159,0.0001323744,0.0001154225,0.00007269957,0.00002422695,0.0001653497,0.00002675213,0.000297498,0.00001299493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001891362,"about_ca_system_score_gemma":0.00005979555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001426312,"about_ca_topic_score_gemma":0.0001295942,"domain_scores_codex":[0.999044,0.00000817922,0.0005244159,0.0001235049,0.00008635585,0.0002135458],"domain_scores_gemma":[0.9991865,0.0002270948,0.0001325265,0.0001165772,0.0002777213,0.00005962487],"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":[0.000122982,0.00007689776,0.002021053,0.00002323491,0.0001503854,0.000005475511,0.0003912074,0.02343816,0.1662987,0.001230042,0.000548424,0.8056934],"study_design_scores_gemma":[0.001437143,0.00007639782,0.002018098,0.00005964065,0.00001776721,0.00007160729,0.0002228534,0.8746365,0.01268003,0.002470501,0.1059308,0.0003785765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7821897,0.00009164523,0.2119822,0.000236742,0.004491663,0.0005012085,0.0001434724,0.0001265286,0.0002368871],"genre_scores_gemma":[0.8841867,0.00002168681,0.1149509,0.00008113509,0.0004982069,0.0001391533,0.00004989973,0.00004040685,0.00003193624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8511984,"threshold_uncertainty_score":0.539807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02982473175676574,"score_gpt":0.3049067107981763,"score_spread":0.2750819790414106,"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."}}