{"id":"W1989377671","doi":"10.1109/ita.2010.5454108","title":"Delay performance of CSMA policies in multihop wireless networks: A new perspective","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer network; Computer science; Carrier sense multiple access with collision avoidance; Network packet; Wireless network; Interference (communication); Throughput; Wireless; Channel (broadcasting); Transmission delay; Propagation delay; Exponential backoff; Distributed computing; Telecommunications","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":[0.002996656,0.001036996,0.000889954,0.001171573,0.0005649439,0.002058002,0.001159085,0.001301296,0.001450721],"category_scores_gemma":[0.01666504,0.0003912355,0.0004295664,0.001050036,0.001890837,0.003695343,0.001007539,0.002306879,0.0002181917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002340844,"about_ca_system_score_gemma":0.001407107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002074002,"about_ca_topic_score_gemma":0.000812854,"domain_scores_codex":[0.9983945,0.0004672845,0.00006121249,0.0001971468,0.0005934287,0.0002863867],"domain_scores_gemma":[0.9871299,0.01006015,0.0009033509,0.0005205791,0.001111943,0.0002740827],"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":[0.0002529756,0.000154032,0.00133544,0.0002521466,0.00007072817,0.0001250739,0.0002323626,0.7285569,0.008451092,0.2277994,0.001969693,0.03080023],"study_design_scores_gemma":[0.00001721521,0.0001656554,0.0002551118,0.00003459652,0.00002028587,0.00007103655,0.00007744336,0.957868,0.002611006,0.03690321,0.001951608,0.00002473061],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1119559,0.01283285,0.8472784,0.004293768,0.0006976299,0.00006892627,0.0001320802,0.0002556334,0.02248484],"genre_scores_gemma":[0.9583762,0.006124324,0.03083514,0.00041567,0.000659648,0.00004138151,0.00003427462,0.00008658585,0.003426865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002996656,"threshold_uncertainty_score":0.01698405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004490342186270684,"score_gpt":0.2128047172469222,"score_spread":0.2083143750606515,"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."}}