{"id":"W2744575178","doi":"10.1109/tac.2019.2929206","title":"Push-Sum on Random Graphs: Almost Sure Convergence and Convergence Rate","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Sequence (biology); Convergence of random variables; Ergodicity; Convergence (economics); Random graph; Bounded function; Rate of convergence; Random matrix; Discrete mathematics; Combinatorics; Zero (linguistics); Directed graph; Stochastic matrix; Random variable; Markov chain; Computer science; Graph; Eigenvalues and eigenvectors","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008273847,0.001791747,0.002164009,0.001973146,0.001119344,0.002049069,0.002223184,0.002150269,0.002457752],"category_scores_gemma":[0.04291916,0.0006749973,0.001535362,0.001306243,0.003926945,0.005268711,0.003725669,0.003053456,0.0006383367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001297025,"about_ca_system_score_gemma":0.001072321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041902,"about_ca_topic_score_gemma":0.0004366892,"domain_scores_codex":[0.9970476,0.001361638,0.000134381,0.0005394083,0.0006538909,0.0002631439],"domain_scores_gemma":[0.9660879,0.02762901,0.001889225,0.001340163,0.002133274,0.0009204782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001613233,0.0000787907,0.001059289,0.0003805826,0.0001547439,0.0002437005,0.000358926,0.4772967,0.003869981,0.495356,0.00109829,0.01994176],"study_design_scores_gemma":[0.00001386957,0.000062245,0.00009004301,0.00003061433,0.00001691108,0.00007204259,0.00004373372,0.8829302,0.001273251,0.1150524,0.0003955633,0.00001898327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03774063,0.0006646125,0.9568884,0.0004741973,0.00006006883,0.00007181313,0.0000501957,0.0002421739,0.003807955],"genre_scores_gemma":[0.8306062,0.002033121,0.1596265,0.0004486111,0.000193326,0.0005448582,0.0001937282,0.0004528213,0.00590098],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008273847,"threshold_uncertainty_score":0.04375684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008481407606589091,"score_gpt":0.2170633990432242,"score_spread":0.2085819914366351,"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."}}