{"id":"W4303044269","doi":"10.1002/rnc.6381","title":"Leaderless output sign consensus of heterogeneous multi‐agent systems over signed graphs","year":2022,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Natural Science Foundation of China","keywords":"Adjacency matrix; Sign (mathematics); Multi-agent system; Control theory (sociology); Observer (physics); Computer science; Consensus; Graph; Controller (irrigation); Directed graph; Signed graph; Topology (electrical circuits); State (computer science); Network topology; Graph theory; Mathematics; Control (management); Theoretical computer science; Algorithm; Artificial intelligence; Combinatorics","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":[0.0007483813,0.0005344577,0.000515908,0.0004473498,0.0003277774,0.0009739394,0.0007188278,0.0005552285,0.0007275576],"category_scores_gemma":[0.003415036,0.0001466842,0.0003536573,0.0003648806,0.0008571302,0.0009942178,0.0008595121,0.0005812855,0.0001123528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004984086,"about_ca_system_score_gemma":0.0005769721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001684047,"about_ca_topic_score_gemma":0.0009015932,"domain_scores_codex":[0.9993083,0.0002256352,0.0000403324,0.0001397875,0.0002052194,0.000080636],"domain_scores_gemma":[0.9981573,0.0007625262,0.0004254364,0.0001553013,0.0003800564,0.0001193827],"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":[0.0001627848,0.00005990632,0.001020081,0.00008574003,0.00004586052,0.0004300957,0.0001489555,0.9018807,0.01971771,0.05225911,0.0003962787,0.02379278],"study_design_scores_gemma":[0.00001047166,0.00004497253,0.0001269017,0.000002476598,0.000005213738,0.00001677999,0.0000228209,0.9878426,0.001798665,0.009917948,0.0002056485,0.000005487503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.127363,0.00008398261,0.869214,0.0001379713,0.00005082419,0.00003854951,0.000029836,0.0001656496,0.002916092],"genre_scores_gemma":[0.9875798,0.00005328268,0.01114214,0.00002180239,0.0000115274,0.00002752408,0.0000276331,0.00001155242,0.001124738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001684047,"threshold_uncertainty_score":0.003957868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02796808405458243,"score_gpt":0.2539563153131472,"score_spread":0.2259882312585647,"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."}}