{"id":"W2099671751","doi":"10.1109/twc.2010.100510.091821","title":"Energy Efficient Quality of Service Traffic Scheduler for MIMO Downlink SVD Channels","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Quality of service; Scheduling (production processes); Computer network; Telecommunications link; MIMO; Channel (broadcasting); Queue; Network packet; Energy consumption; Throughput; Real-time computing; Mathematical optimization; Wireless; Telecommunications; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002239086,0.000254698,0.0003404296,0.0002128037,0.0003465039,0.00002614879,0.0007824022,0.0002254141,0.0000346922],"category_scores_gemma":[0.000006257189,0.0002915297,0.0001673123,0.0006970369,0.0001454203,0.0001358414,0.000005541501,0.0004970843,0.00001048813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006256961,"about_ca_system_score_gemma":0.00004454421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004175078,"about_ca_topic_score_gemma":0.001156246,"domain_scores_codex":[0.9985568,0.00008262192,0.0006233566,0.0002404673,0.000192458,0.0003042903],"domain_scores_gemma":[0.9970511,0.0005961541,0.0001369983,0.001770311,0.0003331236,0.0001123409],"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":[0.00002524619,0.0003222998,7.651395e-7,0.0000688082,0.00006113581,4.160048e-8,0.0002715244,0.9491223,0.01976647,0.00283807,0.00002393698,0.02749942],"study_design_scores_gemma":[0.000623495,0.00002621128,0.00001679592,0.0000502067,0.00003916,0.00000157616,0.00008005823,0.9661855,0.03163098,0.00007634707,0.0009817674,0.0002878739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1276772,0.00009658887,0.8698,0.0005001474,0.0007776988,0.0003772699,0.0001608779,0.000420474,0.0001897883],"genre_scores_gemma":[0.9663461,0.0003276967,0.03246702,0.00008614117,0.00004912106,0.0005136481,0.00008308917,0.00008108714,0.00004610583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8386689,"threshold_uncertainty_score":0.9999537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695400048309945,"score_gpt":0.2770110392759093,"score_spread":0.2500570387928098,"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."}}