{"id":"W2111336126","doi":"10.1109/tvt.2011.2158674","title":"Dynamic QoS-Based Bandwidth Allocation Framework for Broadband Wireless Networks","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Toronto","funders":"","keywords":"Computer network; WiMAX; Quality of service; Computer science; Wireless broadband; Interoperability; Dynamic bandwidth allocation; Bandwidth allocation; Wireless network; Radio resource management; Broadband networks; Mobile broadband; Resource allocation; Wireless; Broadband; 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":[0.002396249,0.000981551,0.0006166958,0.0007478301,0.0007531921,0.00167663,0.002321607,0.000968961,0.001565414],"category_scores_gemma":[0.00201046,0.0003047655,0.0005489528,0.0008294967,0.00134591,0.001923043,0.001166653,0.001751709,0.0005895112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002020058,"about_ca_system_score_gemma":0.002599583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005591018,"about_ca_topic_score_gemma":0.004460778,"domain_scores_codex":[0.9986516,0.0004019161,0.00007894816,0.0002017816,0.0005310557,0.0001347441],"domain_scores_gemma":[0.9995031,0.0001670632,0.00005414391,0.00006445163,0.0001578083,0.00005347648],"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":[0.00004798367,0.00009867473,0.0002757309,0.00009483106,0.0000271566,0.0001580867,0.0001909214,0.3219135,0.008329105,0.5909899,0.003999367,0.07387465],"study_design_scores_gemma":[0.00001670727,0.00004556904,0.00009270347,0.00002034395,0.0000153735,0.00007581701,0.00002738303,0.9158607,0.001187428,0.06569593,0.0169405,0.00002157846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001942914,0.0006244321,0.9936639,0.0002392719,0.00009367728,0.00005202859,0.00002974011,0.0002597382,0.003094414],"genre_scores_gemma":[0.3041176,0.002256102,0.6843002,0.0003088198,0.0005245737,0.000596895,0.0002523404,0.0002036381,0.007439847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005591018,"threshold_uncertainty_score":0.01465666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009180173617254643,"score_gpt":0.2187033384236196,"score_spread":0.209523164806365,"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."}}