{"id":"W1976445502","doi":"10.1109/wimob.2010.5645044","title":"Scheduling and resource allocation for multiclass services in LTE uplink systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Quality of service; Computer science; Telecommunications link; Scheduling (production processes); Computer network; Resource allocation; Distributed computing; Limiting; Mathematical optimization; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001002248,0.00007313587,0.00008149815,0.00005126812,0.00002712007,0.00003220776,0.00004616386,0.00007601344,7.996337e-7],"category_scores_gemma":[0.000009285359,0.00007550122,0.000007573617,0.00008712152,0.000007843767,0.0001487689,0.0000104294,0.0000935135,0.000001322677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001499354,"about_ca_system_score_gemma":0.000002205386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000125788,"about_ca_topic_score_gemma":0.0001648931,"domain_scores_codex":[0.9995891,0.00000422669,0.0001404832,0.0001100188,0.00003769996,0.0001184432],"domain_scores_gemma":[0.9997611,0.00006497954,0.00001910772,0.00009866254,0.00002595819,0.00003020737],"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":[0.000003384278,0.000003044865,0.0005519673,0.000127385,0.000003120148,1.142534e-7,0.00009833094,0.9882241,0.007537192,0.001382783,0.000004152143,0.002064453],"study_design_scores_gemma":[0.0002835074,0.000004016033,0.0002616543,0.00003693387,0.000002705933,9.816503e-7,0.0001410474,0.9976481,0.0007627877,0.00003961632,0.0007315938,0.00008712378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3847222,0.0001646756,0.6140562,0.00003623562,0.0001820886,0.0002909617,7.816931e-7,0.0001945909,0.0003523102],"genre_scores_gemma":[0.9098929,0.00001960043,0.08985451,0.00001257615,0.00008385229,0.0000500046,0.00001641403,0.00002402309,0.00004611093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5251707,"threshold_uncertainty_score":0.3078851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004601274714918609,"score_gpt":0.2078291960919841,"score_spread":0.2032279213770655,"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."}}