{"id":"W2101309139","doi":"10.1109/glocom.2009.5425462","title":"QoS-Driven Node Cooperative Resource Allocation for Wireless Mesh Networks with Service Differentiation","year":2009,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer network; Computer science; Quality of service; Resource allocation; Wireless mesh network; Node (physics); Throughput; Resource management (computing); Network packet; Differentiated services; Wireless network; Provisioning; Distributed computing; Wireless; Telecommunications; 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":[0.001023564,0.000251993,0.0002449317,0.0002618718,0.0003623041,0.0002943944,0.0006978459,0.0003140961,0.0005248009],"category_scores_gemma":[0.001605182,0.0001215119,0.0001902763,0.0003790625,0.0005754132,0.0004691415,0.0006435853,0.00031729,0.0001083448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006642067,"about_ca_system_score_gemma":0.0005960555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009015361,"about_ca_topic_score_gemma":0.001407527,"domain_scores_codex":[0.9996877,0.0001514968,0.00001031068,0.000029796,0.00008820335,0.00003251005],"domain_scores_gemma":[0.9996213,0.0002305288,0.00003929317,0.00003978259,0.0000493268,0.00001974087],"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":[0.0001373724,0.00007122302,0.0006281601,0.00007058342,0.0000313754,0.0001339212,0.0001885645,0.8011274,0.0192784,0.09488758,0.0008598706,0.08258556],"study_design_scores_gemma":[0.000009265619,0.00003062804,0.00007417286,0.000002759933,0.00000463836,0.00002120122,0.00001186235,0.9864223,0.001055495,0.01175237,0.0006111327,0.000004189962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05192275,0.0003798998,0.9452083,0.0001322496,0.00002344832,0.00003782248,0.000007615519,0.00005786615,0.002230071],"genre_scores_gemma":[0.9007932,0.0002129331,0.09746432,0.00005482763,0.00002031931,0.00008208182,0.00001741218,0.00001219612,0.001342755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001023564,"threshold_uncertainty_score":0.005413175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02496329496541396,"score_gpt":0.2575997868926869,"score_spread":0.232636491927273,"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."}}