{"id":"W2097962411","doi":"10.1109/mwc.2002.998522","title":"Dynamic bandwidth allocation with fair scheduling for WCDMA systems","year":2002,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Government of Canada; Australian Government","keywords":"Computer science; Computer network; Scheduling (production processes); Code division multiple access; Quality of service; Broadband networks; Network packet; W-CDMA; Bandwidth (computing); Exploit; Bandwidth allocation; Wireless; Wireless network; Broadband; Distributed computing; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00214495,0.0008131121,0.0008149869,0.0009048049,0.001220781,0.00163388,0.001381041,0.0008234591,0.002037541],"category_scores_gemma":[0.007007932,0.0003726343,0.0003367649,0.001128637,0.001097487,0.001439848,0.0009982283,0.001031384,0.0003119721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002407244,"about_ca_system_score_gemma":0.002391286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007461156,"about_ca_topic_score_gemma":0.006530282,"domain_scores_codex":[0.9985344,0.0004112342,0.00005458632,0.0001560607,0.0006050993,0.0002385179],"domain_scores_gemma":[0.9983271,0.0008812696,0.0001388702,0.0002617245,0.0003089169,0.00008214503],"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":[0.0002066651,0.0000612351,0.0003365767,0.0001005708,0.00004172304,0.0001459511,0.00008477056,0.7362116,0.006188488,0.1664907,0.002598571,0.08753313],"study_design_scores_gemma":[0.00001999289,0.0000200294,0.00005972334,0.000008591467,0.000009562325,0.0000259045,0.000007951342,0.9640511,0.001342522,0.03217819,0.002265454,0.00001094915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01028518,0.001151719,0.9839001,0.0001867141,0.0001854167,0.00009310812,0.00002864415,0.0003615855,0.003807605],"genre_scores_gemma":[0.826316,0.001236785,0.1673381,0.0001294749,0.0002892157,0.0002662348,0.00007791406,0.00008264703,0.004263652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007461156,"threshold_uncertainty_score":0.01746583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0550840306179374,"score_gpt":0.2986498327629833,"score_spread":0.2435658021450459,"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."}}