{"id":"W2119741378","doi":"10.1109/tsp.2008.2010376","title":"Accelerated Distributed Average Consensus via Localized Node State Prediction","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Convergence (economics); Node (physics); Rate of convergence; Mathematical optimization; Mathematics; Upper and lower bounds; Mixing (physics); Focus (optics); Computer science; Matrix (chemical analysis); State (computer science); Eigenvalues and eigenvectors; Convex optimization; Regular polygon; Algorithm; Applied 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002852936,0.0003920321,0.0004143183,0.0002478866,0.0009760337,0.0002965308,0.000595868,0.0001613924,0.00004756442],"category_scores_gemma":[0.00000710798,0.0003894585,0.0001613248,0.001148334,0.000149032,0.0007396911,0.000004663565,0.0004838617,0.0001324656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002670155,"about_ca_system_score_gemma":0.0003144207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007759582,"about_ca_topic_score_gemma":0.000007422123,"domain_scores_codex":[0.9969543,0.0002232026,0.0007370659,0.0007571488,0.0007067575,0.0006215692],"domain_scores_gemma":[0.9984465,0.0001353656,0.0002751783,0.0004657892,0.0004056161,0.0002715442],"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":[0.0005342267,0.001126486,0.0001576916,0.0001584216,0.0002785908,0.0005309734,0.001551148,0.7395652,0.05176733,0.00002403998,0.0007515591,0.2035543],"study_design_scores_gemma":[0.002493703,0.0001268767,0.0002260381,0.0001147897,0.00003166425,0.0002770275,0.00001813395,0.9546586,0.04085434,0.00008241573,0.0007130947,0.0004032878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01737863,0.00007913927,0.9798226,0.0002557104,0.0005003758,0.000461403,0.0002992362,0.001047685,0.0001552385],"genre_scores_gemma":[0.99627,0.00001044862,0.003108978,0.000183555,0.00005111652,0.00008411079,0.0000380788,0.00003507444,0.0002186644],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9788913,"threshold_uncertainty_score":0.9998558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03272412673507932,"score_gpt":0.2475680932402552,"score_spread":0.2148439665051759,"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."}}