{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00113633,0.0005790159,0.0008496309,0.0004536983,0.000456578,0.0005135738,0.001390657,0.0005703513,0.0008910117],"category_scores_gemma":[0.003501659,0.0003276489,0.000364633,0.0004669026,0.000763913,0.0012643,0.001248476,0.001087783,0.0002899866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006211619,"about_ca_system_score_gemma":0.001007394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002785941,"about_ca_topic_score_gemma":0.002251137,"domain_scores_codex":[0.9992482,0.0001914096,0.0000246635,0.0001502721,0.000314283,0.0000712035],"domain_scores_gemma":[0.9987817,0.0005929932,0.0001505055,0.0001992431,0.0002347106,0.00004082271],"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":[0.00006909119,0.00002926696,0.0004169047,0.00004516443,0.00001762656,0.00005249243,0.0001332144,0.9234207,0.005624353,0.01490633,0.0005859808,0.05469882],"study_design_scores_gemma":[0.0000049388,0.00001986601,0.00003634611,0.000001956677,0.000002439989,0.000006817332,0.000004834087,0.9965721,0.0008990682,0.002138152,0.0003106956,0.00000280926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01381835,0.00006774954,0.9845176,0.00006234504,0.00001809109,0.00001502462,0.000007058917,0.0003449967,0.001148832],"genre_scores_gemma":[0.8297881,0.0001634344,0.1665778,0.00008058442,0.00005081863,0.0001144443,0.00005683595,0.00006853213,0.003099421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002785941,"threshold_uncertainty_score":0.006009579,"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."}}