{"id":"W4293074843","doi":"10.11159/cdsr22.128","title":"Scaled Consensus Of Hybrid Multi-Agent Systems","year":2022,"lang":"en","type":"article","venue":"Proceedings of the International Conference of Control, Dynamic systems, and Robotics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multi-agent system; Computer science; Distributed computing; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0003484159,0.000130881,0.0003577666,0.0001172826,0.00006282901,0.00003810086,0.0004097986,0.00003122658,0.000008571968],"category_scores_gemma":[0.00009463275,0.0001102825,0.00007165725,0.00008680437,0.00009770074,0.00004540526,0.00009099724,0.0001360916,3.306891e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006903628,"about_ca_system_score_gemma":0.00004334232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004988153,"about_ca_topic_score_gemma":0.000001333661,"domain_scores_codex":[0.9986904,0.00001578481,0.0006043322,0.0001305887,0.0004414848,0.0001174269],"domain_scores_gemma":[0.9986705,0.00007716312,0.0004057752,0.00008345458,0.0007243452,0.00003880386],"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":[0.00003482484,0.00004318665,0.002289017,0.0003508238,0.0002233677,5.17196e-7,0.0001369477,0.9801047,0.005718146,0.01096656,0.00007113356,0.00006081156],"study_design_scores_gemma":[0.001011258,0.00003672947,0.0002657046,0.0001858152,0.00005533805,0.0000544156,0.001306455,0.9966336,0.0002632716,0.00004889366,0.00003604904,0.0001024736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8779576,0.00414754,0.101838,0.0008035849,0.009076785,0.001577325,0.0008545695,0.0001949049,0.003549764],"genre_scores_gemma":[0.9970253,0.00007406264,0.00249604,0.000007142492,0.00002855426,0.00002275836,0.000005608803,0.00001699136,0.0003235919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1190677,"threshold_uncertainty_score":0.4497191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01849711112236221,"score_gpt":0.224327608944505,"score_spread":0.2058304978221428,"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."}}