{"id":"W2120968943","doi":"10.1109/tcomm.2013.042313.120770","title":"Throughput Upper-Bound of Slotted CSMA Systems with Unsaturated Finite Population","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Upper and lower bounds; Throughput; Exponential backoff; Computer science; Population; Algorithm; Markov process; Markov chain; Protocol (science); Computer network; Mathematics; Statistics","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":[0.0001407401,0.0001683868,0.0002248839,0.0001552495,0.0004710488,0.0002141586,0.001320026,0.000102815,0.00003206573],"category_scores_gemma":[0.000003117133,0.0001419011,0.0000708866,0.0009173374,0.0001146173,0.0007085176,0.000009835241,0.0003180426,0.00006501313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005435142,"about_ca_system_score_gemma":0.00006290762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001726359,"about_ca_topic_score_gemma":0.0002244236,"domain_scores_codex":[0.9986576,0.0002511642,0.0004033561,0.0002389355,0.0002380998,0.0002108023],"domain_scores_gemma":[0.9966319,0.0004338485,0.0002029068,0.002362663,0.0002912012,0.00007749817],"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":[0.0001145656,0.002887164,0.001058828,0.0002352508,0.0006369767,0.000003191272,0.003442737,0.7201082,0.004035449,0.07658763,0.001779424,0.1891106],"study_design_scores_gemma":[0.0009194064,0.0003995395,0.007671156,0.0003811373,0.00004282376,0.00002546247,0.0001382345,0.9850094,0.001453016,0.001126934,0.002386859,0.0004460542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006424579,0.00009589722,0.9874772,0.001337229,0.0001903141,0.003186363,0.00001691866,0.000232064,0.001039438],"genre_scores_gemma":[0.9774879,0.00007519696,0.01944028,0.00007279206,0.00001432937,0.002583962,0.00001708695,0.00001788837,0.0002906088],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9710633,"threshold_uncertainty_score":0.578656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820872018376837,"score_gpt":0.2619949986034854,"score_spread":0.233786278419717,"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."}}