{"id":"W1982567035","doi":"10.48550/arxiv.1105.1668","title":"Convergence Time Analysis of Quantized Gossip Consensus on Digraphs","year":2011,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Ministry of Education, Culture, Sports, Science and Technology","keywords":"Convergence (economics); Gossip; Markov chain; Upper and lower bounds; Time complexity; Interval (graph theory); Markov process; Computer science; Mathematics; Lyapunov function; Algorithm; Mathematical optimization; 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":[0.001842214,0.0003981133,0.0006563819,0.0007686397,0.0003636846,0.00061974,0.0006539723,0.0004438393,0.001035369],"category_scores_gemma":[0.01081231,0.0002425409,0.0002811578,0.0003966538,0.001405224,0.001247121,0.0007892952,0.000847152,0.0001015644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001273492,"about_ca_system_score_gemma":0.0005145179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002288505,"about_ca_topic_score_gemma":0.001029848,"domain_scores_codex":[0.9995408,0.0001553504,0.00002290411,0.00007216496,0.0001358543,0.00007304905],"domain_scores_gemma":[0.9944142,0.004016463,0.0004821318,0.0002555868,0.0005735351,0.0002580793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001665215,0.00002544568,0.001143494,0.0001096971,0.00003621541,0.0001423136,0.0003662928,0.8104659,0.008898453,0.1698128,0.0004693316,0.008363665],"study_design_scores_gemma":[0.000006252951,0.00001538959,0.000119327,0.00000319541,0.000003249797,0.000006683482,0.00001522857,0.9819809,0.0005929442,0.01716961,0.00008357536,0.000003618309],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4742136,0.0003506552,0.5202047,0.0004278876,0.00003662645,0.00004155414,0.00008350531,0.0003625563,0.004278872],"genre_scores_gemma":[0.9893083,0.0001056495,0.009748415,0.00002793944,0.000008238988,0.00002967737,0.00004332168,0.00002837244,0.0007000265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002288505,"threshold_uncertainty_score":0.009742677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08673103443744931,"score_gpt":0.1907673095906027,"score_spread":0.1040362751531534,"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."}}