{"id":"W2116066327","doi":"10.1109/tsp.2010.2043127","title":"Optimization and Analysis of Distributed Averaging With Short Node Memory","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Convergence (economics); Rate of convergence; Node (physics); Algorithm; Acceleration; Mathematics; Network topology; Computer science; Grid; Mathematical optimization; Focus (optics); Series (stratigraphy); Topology (electrical circuits); 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":[0.001475854,0.00085961,0.0009884759,0.0006643229,0.0004710037,0.000833411,0.001191859,0.0008793972,0.002262134],"category_scores_gemma":[0.007209369,0.0003813188,0.0004771534,0.0007301499,0.001301088,0.001533978,0.0009858228,0.0008297165,0.0003365526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001278394,"about_ca_system_score_gemma":0.0009909247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004641871,"about_ca_topic_score_gemma":0.002675202,"domain_scores_codex":[0.9993004,0.0001708236,0.0000284002,0.0001327701,0.0002679732,0.00009976547],"domain_scores_gemma":[0.9975332,0.001568762,0.0003090235,0.0001489893,0.0003594852,0.00008043728],"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":[0.00003723831,0.00001511264,0.0003077885,0.00005220121,0.00002129204,0.00005033612,0.00003625368,0.94116,0.001233559,0.04774147,0.0007655057,0.008579186],"study_design_scores_gemma":[0.000002755816,0.000007136109,0.00004285792,0.000002273562,0.000002267735,0.00000418417,0.000002827838,0.9891031,0.000153003,0.01051145,0.0001655974,0.000002527186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02135818,0.0006584958,0.9712408,0.0004168636,0.00006453736,0.00003296145,0.00006127115,0.0002373248,0.005929583],"genre_scores_gemma":[0.9232013,0.0009703919,0.06587934,0.0001985236,0.0001727364,0.0002519427,0.0001808154,0.0001936783,0.008951211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004641871,"threshold_uncertainty_score":0.009275496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108059728990224,"score_gpt":0.2313950402271037,"score_spread":0.2203144429372014,"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."}}