{"id":"W2013154696","doi":"10.1016/j.tcs.2015.01.024","title":"A characterization of oblivious message adversaries for which Consensus is solvable","year":2015,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Henan Institute of Science and Technology; Agence Nationale de la Recherche","keywords":"Network topology; Adversary; Computer science; Set (abstract data type); Theoretical computer science; Characterization (materials science); Message passing; Consensus algorithm; Topology (electrical circuits); Mathematics; Computer network; Discrete mathematics; Distributed computing; Algorithm; Computer security; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001521666,0.0001569312,0.0002922006,0.0001145473,0.0001964917,0.0002905447,0.001498952,0.00006140296,0.000006302282],"category_scores_gemma":[0.0001652215,0.000132491,0.00005538221,0.001212228,0.001153884,0.0004771479,0.0004226734,0.00008026414,0.00001650384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004522796,"about_ca_system_score_gemma":0.0003677791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000731294,"about_ca_topic_score_gemma":8.726485e-7,"domain_scores_codex":[0.9979278,0.00006225535,0.0003730524,0.000550918,0.0006287677,0.0004571693],"domain_scores_gemma":[0.997683,0.0001411624,0.0001618961,0.0006771599,0.001075899,0.0002608399],"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":[0.00002097015,0.00006049087,0.00005384566,0.00002370272,0.000005839649,0.000002227242,0.00131161,0.0000709079,0.005820463,0.9880028,0.0003192845,0.004307896],"study_design_scores_gemma":[0.000764437,0.0003840108,0.0003787228,0.00006941761,0.000007800023,0.00002966038,0.0000271756,0.9139033,0.03134159,0.05088396,0.001930749,0.0002791523],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06885799,0.00001976815,0.9275189,0.001233737,0.0006992924,0.000298954,0.00003925469,0.0001009126,0.001231179],"genre_scores_gemma":[0.9434998,0.000001285813,0.05607229,0.000304967,0.00006788192,0.0000141759,0.000004806297,0.000006193646,0.00002858316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9371188,"threshold_uncertainty_score":0.5402828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01790132295529213,"score_gpt":0.2537304377306758,"score_spread":0.2358291147753837,"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."}}