{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000328858,0.0002698805,0.0003832708,0.0001683016,0.0003278801,0.0004255706,0.0004034263,0.0002189085,0.000003602727],"category_scores_gemma":[0.00001519858,0.0002410275,0.00005707934,0.0004447382,0.0001181162,0.0003575658,0.00001407316,0.0004263262,0.00001402878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002970551,"about_ca_system_score_gemma":0.00005023234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008330481,"about_ca_topic_score_gemma":0.0006341428,"domain_scores_codex":[0.9981561,0.0001045604,0.0004769872,0.0006009632,0.0002612285,0.0004002033],"domain_scores_gemma":[0.9988927,0.0002008398,0.0001217373,0.0004486487,0.00008715433,0.0002489781],"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":[0.001745654,0.005134346,0.01468133,0.001899634,0.0005384884,0.001357251,0.00756092,0.8342838,0.03234079,0.02703882,0.01073737,0.06268159],"study_design_scores_gemma":[0.003277511,0.000139058,0.006704671,0.0001676318,0.00001326381,0.0003786284,0.0002849828,0.9844724,0.0002043638,0.0002216104,0.00356487,0.0005709984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1933999,0.0001827453,0.8037513,0.0003256351,0.00124299,0.0004410576,0.0004180347,0.000129414,0.0001089325],"genre_scores_gemma":[0.9993268,0.00004621318,0.0002614976,0.00004556803,0.00004575273,0.0001320589,0.00002058913,0.00001143111,0.0001101492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8059268,"threshold_uncertainty_score":0.9828816,"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."}}