{"id":"W2162375717","doi":"10.1109/glocomw.2008.ecp.35","title":"Uplink Scheduling in Wireless Mesh Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Wireless mesh network; Maximum throughput scheduling; Fairness measure; Computer science; Computer network; Wireless broadband; Scheduling (production processes); Throughput; Wireless network; Switched mesh; Router; Service set; Mesh networking; Max-min fairness; Wireless; Distributed computing; Round-robin scheduling; Quality of service; Dynamic priority scheduling; Wi-Fi array; Telecommunications; Resource allocation; Engineering","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":[0.0002520401,0.0001324904,0.0001797946,0.00007476943,0.00009530238,0.0000527115,0.0008694269,0.000107988,0.00003968648],"category_scores_gemma":[0.000008530962,0.0001245893,0.0000488013,0.0006510716,0.00004397499,0.0003831987,0.0003095165,0.0002912743,0.00006930676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004243982,"about_ca_system_score_gemma":0.00005359142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000601504,"about_ca_topic_score_gemma":0.00006224488,"domain_scores_codex":[0.998683,0.00004293688,0.00026285,0.0004065236,0.0001750717,0.0004296317],"domain_scores_gemma":[0.9991329,0.00009174037,0.00003915469,0.0005979247,0.0000357899,0.0001025257],"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":[0.000009342202,0.0001616571,0.02823079,0.000008010908,0.0000182341,0.0004555083,0.0005516476,0.2969235,0.00008790031,0.5834216,0.003501901,0.08662987],"study_design_scores_gemma":[0.0002407286,0.00001726727,0.003274674,0.00001606769,6.251822e-7,0.00005338679,0.000004324688,0.9956309,0.0001095726,0.0003649577,0.0001260303,0.0001614918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.110283,0.00008555179,0.8835034,0.0002338981,0.0003406788,0.0001267042,2.846302e-8,0.0002305005,0.00519624],"genre_scores_gemma":[0.9437262,0.0001227462,0.0549596,0.000584794,0.0001504593,0.00002084934,8.779742e-7,0.00001037503,0.000424086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8334432,"threshold_uncertainty_score":0.5080603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01717384355399175,"score_gpt":0.2313987756978457,"score_spread":0.2142249321438539,"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."}}