{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001092066,0.0003975685,0.0005279148,0.0004439577,0.001256171,0.0004535182,0.0009256321,0.0002519316,0.00001841846],"category_scores_gemma":[0.00006581598,0.0004219846,0.0003426633,0.00117361,0.00005801998,0.0005263617,0.00001887201,0.0007914428,0.00005998173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009402274,"about_ca_system_score_gemma":0.0003837491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001094552,"about_ca_topic_score_gemma":0.000009167717,"domain_scores_codex":[0.9960982,0.0003363595,0.001652125,0.0003519299,0.0008737079,0.0006876777],"domain_scores_gemma":[0.9973032,0.0005030947,0.0007682873,0.0008790627,0.000276158,0.0002702244],"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":[0.0002012426,0.0003398467,0.00001125932,0.00004895114,0.0002263537,0.000005652636,0.0007623599,0.973373,0.0001795598,0.0003861949,0.01283687,0.01162872],"study_design_scores_gemma":[0.005886635,0.0006384337,0.000003962678,0.00005688884,0.00007802548,0.00004170803,0.001717917,0.9434417,0.001754567,0.00001573325,0.04585761,0.0005068519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01693311,0.00002516317,0.965454,0.0003436663,0.01020102,0.002810309,0.003613524,0.0005154406,0.0001037257],"genre_scores_gemma":[0.996662,0.000005169564,0.0007543513,0.0002074054,0.0001904298,0.00159339,0.0002397758,0.00003058814,0.0003168459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9797289,"threshold_uncertainty_score":0.9998232,"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."}}