{"id":"W2170398686","doi":"10.1109/tpds.2010.162","title":"Consensus and Mutual Exclusion in a Multiple Access Channel","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; Mutual exclusion; Collision detection; Channel (broadcasting); Collision; Logarithm; Time complexity; Process (computing); Collision problem; Critical section; Mutual information; Algorithm; Theoretical computer science; Distributed computing; Computer network; Mathematics; Artificial intelligence; Computer security","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":[0.005021624,0.00132004,0.00170965,0.001157854,0.001848739,0.00328552,0.001746003,0.002165945,0.003948147],"category_scores_gemma":[0.02678216,0.0007515989,0.001274547,0.001705054,0.003902105,0.006328433,0.003353748,0.002756319,0.0005106936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0027893,"about_ca_system_score_gemma":0.003409255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003500528,"about_ca_topic_score_gemma":0.002049297,"domain_scores_codex":[0.9919136,0.003095949,0.0002863274,0.001421058,0.001740624,0.00154264],"domain_scores_gemma":[0.9370992,0.05461394,0.002563011,0.002878308,0.0017719,0.001073757],"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":[0.0006692307,0.0001615102,0.001213382,0.000182067,0.0000784768,0.0002472975,0.0003813336,0.7756194,0.002291971,0.2062156,0.001099951,0.01183975],"study_design_scores_gemma":[0.00007755041,0.00005074146,0.0001280047,0.000007116388,0.00001511382,0.0000334663,0.00004143784,0.8949542,0.0007948352,0.1033204,0.0005619102,0.00001526163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1617686,0.0004746566,0.824471,0.001727654,0.00008585725,0.0002490715,0.000296241,0.0004874574,0.01043957],"genre_scores_gemma":[0.8497061,0.0003568759,0.1417895,0.0001660694,0.0001704126,0.0006004933,0.000331416,0.0001415536,0.006737669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005021624,"threshold_uncertainty_score":0.02655715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0254939677994357,"score_gpt":0.2571901699211026,"score_spread":0.2316962021216669,"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."}}