{"id":"W4388517756","doi":"10.1109/fuzz52849.2023.10309774","title":"Fuzzy Analysis for Consensus in Federated Learning with Simulated Heuristic Attacks","year":2023,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Silesian University of Technology","keywords":"Computer science; Voting; Heuristics; Fuzzy logic; Heuristic; Artificial intelligence; Data mining; Machine learning; Disadvantage; Image (mathematics)","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":[0.004406503,0.0006121714,0.001100754,0.001237141,0.0009257853,0.001494785,0.001135452,0.001072582,0.002010392],"category_scores_gemma":[0.01073211,0.0003185272,0.0009923181,0.000551117,0.001524089,0.00136361,0.001354862,0.001177163,0.0001929179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002319644,"about_ca_system_score_gemma":0.00164778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004141619,"about_ca_topic_score_gemma":0.002217497,"domain_scores_codex":[0.9976928,0.0008008345,0.0001295927,0.0003800919,0.0007177033,0.0002789745],"domain_scores_gemma":[0.9937297,0.00383451,0.0006257188,0.0005036555,0.001071507,0.000234902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002130574,0.00005191708,0.0007933649,0.00004498841,0.00006582176,0.0001025356,0.0001665982,0.9357266,0.002350718,0.03963137,0.0003044485,0.02054852],"study_design_scores_gemma":[0.000005255953,0.00001859375,0.00004675163,0.000002221213,0.000003747276,0.00000616031,0.00001012802,0.992301,0.000493379,0.00703754,0.00007218185,0.000003117567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04258433,0.00006320851,0.9552188,0.000140019,0.00002175889,0.0000746018,0.00002633797,0.0002241725,0.001646736],"genre_scores_gemma":[0.9383282,0.00004694547,0.05988522,0.00005310389,0.00001549956,0.0001160713,0.00003655908,0.00002966846,0.001488721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004406503,"threshold_uncertainty_score":0.02330405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04275467592447041,"score_gpt":0.3046392584798609,"score_spread":0.2618845825553905,"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."}}