{"id":"W1972151267","doi":"10.1109/icc.2013.6655598","title":"Power-efficient QoS scheduler for LTE uplink","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Telecommunications link; Computer science; Quality of service; Power (physics); Minification; Computer network; Multi-user; Scheduling (production processes); Real-time computing; Mathematical optimization; Mathematics","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":[0.0004055581,0.0003712337,0.0003274219,0.0001788162,0.0003169288,0.000463317,0.0006407172,0.0002232639,0.001307776],"category_scores_gemma":[0.001018491,0.0001629962,0.0001954366,0.00024346,0.0001953945,0.0004200389,0.0003565385,0.000458393,0.0002984093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000656487,"about_ca_system_score_gemma":0.001180952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002827423,"about_ca_topic_score_gemma":0.00536368,"domain_scores_codex":[0.9997016,0.00006775952,0.00001487309,0.00002485972,0.0001443639,0.00004652822],"domain_scores_gemma":[0.999746,0.00009510238,0.00002028908,0.0000262921,0.00009319331,0.0000191537],"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":[0.0002553604,0.0001101297,0.0008272405,0.00008637605,0.00004332926,0.0001462537,0.0001087903,0.7928324,0.04064468,0.03511329,0.003986733,0.1258453],"study_design_scores_gemma":[0.000007761469,0.00001698251,0.00006344106,0.000001404043,0.00000339351,0.00001225394,0.000005290379,0.9963916,0.00156849,0.001316495,0.0006101819,0.000002606276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02970465,0.0005279545,0.9643272,0.0001669497,0.00006607545,0.00005064626,0.00005801574,0.0003908389,0.00470773],"genre_scores_gemma":[0.799858,0.0004201023,0.1961417,0.0000950946,0.00009452767,0.0000645327,0.000096831,0.00006957913,0.003159631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002827423,"threshold_uncertainty_score":0.00562191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00475301591449684,"score_gpt":0.1952163766792786,"score_spread":0.1904633607647817,"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."}}