{"id":"W1982586504","doi":"10.1007/s11277-008-9448-7","title":"A Channel based Fair Scheduling Scheme for Downlink Data Transmission in TD-CDMA Networks","year":2008,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheduling (production processes); Maximum throughput scheduling; Telecommunications link; Throughput; Code division multiple access; Computer network; Fairness measure; Network packet; Channel (broadcasting); Proportionally fair; Data transmission; Wireless; Real-time computing; Dynamic priority scheduling; Round-robin scheduling; Telecommunications; Quality of service; Mathematical optimization","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":[0.002495319,0.0005930852,0.001170619,0.0009577008,0.001852134,0.00142924,0.001828288,0.0006987986,0.002624723],"category_scores_gemma":[0.004959348,0.0004004864,0.0003703481,0.001030722,0.001172891,0.001120303,0.001189203,0.00082012,0.0002800569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002358462,"about_ca_system_score_gemma":0.003196931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008550618,"about_ca_topic_score_gemma":0.01235817,"domain_scores_codex":[0.9990304,0.0002496298,0.00004385468,0.0001263018,0.0003036756,0.0002461729],"domain_scores_gemma":[0.9976861,0.001182012,0.0001072063,0.0002949274,0.0005362103,0.0001935694],"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":[0.0013311,0.0003738924,0.00115239,0.0001708702,0.0001026121,0.0002130604,0.0002332142,0.7260364,0.03313719,0.07176503,0.005553875,0.1599305],"study_design_scores_gemma":[0.00004172209,0.00007181415,0.0001206152,0.000004351333,0.00002127733,0.00002802264,0.00001398255,0.9910713,0.002224868,0.005744376,0.0006409721,0.00001679645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07114502,0.0006278023,0.9238653,0.0002303432,0.0004573784,0.0001476867,0.0001432286,0.0006608188,0.002722427],"genre_scores_gemma":[0.9035693,0.0001935614,0.09397577,0.0001068387,0.0001592324,0.0001050783,0.00006015051,0.00006308187,0.001766997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008550618,"threshold_uncertainty_score":0.01711196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07385997584558751,"score_gpt":0.2848493049720901,"score_spread":0.2109893291265026,"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."}}