{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000286325,0.00009606874,0.00008464042,0.00003651761,0.00003325693,0.00002396328,0.0000660684,0.0000526567,0.0005637427],"category_scores_gemma":[0.00001028008,0.00008936706,0.00003242001,0.00009898867,0.00001005085,0.00009474505,0.0000133088,0.00005190916,0.0002670295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003452073,"about_ca_system_score_gemma":0.00000349216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001032371,"about_ca_topic_score_gemma":3.994639e-7,"domain_scores_codex":[0.9994907,0.000002275358,0.000127595,0.0001097211,0.00005522225,0.0002144311],"domain_scores_gemma":[0.9996971,0.00003349424,0.00001276897,0.0001479459,0.00005650832,0.00005215009],"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":[9.383387e-7,0.000007565332,0.00001541288,0.000009111238,0.000007319858,7.00386e-8,0.00002057586,0.9892023,0.0007494428,0.002386025,0.005001204,0.002600082],"study_design_scores_gemma":[0.0001917812,0.0000112857,0.0001061896,0.000006898374,0.000002236926,4.274647e-7,0.00001646596,0.9939495,0.001786654,0.0001661724,0.003637081,0.0001253139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01958985,0.00008516204,0.9693936,0.00007791718,0.0004536719,0.0004460144,0.000001059966,0.0004819115,0.009470845],"genre_scores_gemma":[0.7848849,0.00001419048,0.213804,0.00007798181,0.0001237244,0.0001835757,0.00001175413,0.00005062133,0.0008492051],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.765295,"threshold_uncertainty_score":0.6172587,"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."}}