{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001724802,0.0003056979,0.0005165903,0.0005200075,0.0006102307,0.0008995836,0.0005784585,0.0003764485,0.0008495823],"category_scores_gemma":[0.005185254,0.0001745605,0.0001847298,0.0008402594,0.0003313867,0.0009117498,0.0005225151,0.0004086023,0.0001779758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006909881,"about_ca_system_score_gemma":0.0007645167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001892339,"about_ca_topic_score_gemma":0.001254701,"domain_scores_codex":[0.9989275,0.0005289271,0.00005244705,0.00009250593,0.0002943996,0.0001042961],"domain_scores_gemma":[0.9984702,0.0008991597,0.0001508125,0.000191693,0.0002359146,0.00005217347],"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":[0.0002462647,0.00009367198,0.001625453,0.000197535,0.00004576162,0.0001072503,0.0001079123,0.698356,0.008745969,0.04206843,0.002806721,0.245599],"study_design_scores_gemma":[0.00001669985,0.00006500936,0.0002437385,0.00001190343,0.00001518094,0.00003632024,0.00003545632,0.9783478,0.003087668,0.0151096,0.003021448,0.000009272438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06883331,0.004262419,0.9183676,0.0003546352,0.0004507515,0.00008536573,0.00007006174,0.0005199136,0.007055887],"genre_scores_gemma":[0.8981356,0.001474197,0.0980043,0.00007721579,0.0002846969,0.00006968081,0.00006695057,0.00006837973,0.001818946],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001892339,"threshold_uncertainty_score":0.009121776,"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."}}