{"id":"W4226085542","doi":"10.1109/tii.2022.3157595","title":"Distributed Event-Triggered Bipartite Consensus for Multiagent Systems Against Injection Attacks","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Bipartite graph; Multi-agent system; Computer science; Consensus; Distributed computing; Event (particle physics); Computer security; Theoretical computer science; Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001147562,0.0007229025,0.0006904566,0.0003208407,0.000389382,0.0007878768,0.0009524957,0.0009207022,0.001114002],"category_scores_gemma":[0.00258403,0.0002421116,0.0004743187,0.0003212699,0.0008093975,0.00102695,0.001231786,0.0008109543,0.0001610504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006026496,"about_ca_system_score_gemma":0.0007271466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00173171,"about_ca_topic_score_gemma":0.001019439,"domain_scores_codex":[0.9991721,0.0002723457,0.00003734811,0.000177276,0.0002451926,0.00009568688],"domain_scores_gemma":[0.9989593,0.0004572794,0.0002021427,0.00008954782,0.0002303241,0.00006149386],"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":[0.00009281726,0.00003820414,0.0003459061,0.00009277372,0.00004473111,0.000136722,0.00009096578,0.9434712,0.006821885,0.02583939,0.000391072,0.02263437],"study_design_scores_gemma":[0.000005541157,0.00003044705,0.00005108993,0.000002141271,0.000003299197,0.000009607032,0.000006589632,0.9955094,0.0004362319,0.003782161,0.0001606823,0.00000283767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01386492,0.00009468359,0.984183,0.00008585349,0.00002702863,0.00002467424,0.00001276849,0.0001034064,0.001603759],"genre_scores_gemma":[0.9738654,0.0001156054,0.02422391,0.0000645584,0.00002194452,0.00007884886,0.00003840786,0.00001575886,0.00157553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00173171,"threshold_uncertainty_score":0.006069005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05569878821099181,"score_gpt":0.2714209093231147,"score_spread":0.2157221211121229,"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."}}