{"id":"W2156323494","doi":"10.1109/glocomw.2010.5700440","title":"Joint admission control and resource allocation with GoS and QoS in LTE uplink","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Quality of service; Telecommunications link; Computer science; Admission control; Computer network; Resource allocation; Blocking (statistics); Resource management (computing); Scheme (mathematics); Resource (disambiguation); Service (business); Call Admission Control; Joint (building); Telecommunications; Engineering; Wireless; 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":[0.00142638,0.0006506051,0.0008710494,0.0005290691,0.000733208,0.0009604632,0.001231137,0.000631054,0.0005448566],"category_scores_gemma":[0.003536849,0.0002090993,0.0003354598,0.0005600599,0.0008243148,0.001197993,0.0009721168,0.0008298276,0.0001063891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008804,"about_ca_system_score_gemma":0.001270804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006344072,"about_ca_topic_score_gemma":0.004550844,"domain_scores_codex":[0.9987354,0.0004354631,0.00008390534,0.0001155195,0.0003692302,0.0002605335],"domain_scores_gemma":[0.9986946,0.0007251501,0.0001635708,0.0001137113,0.0001964848,0.0001065616],"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":[0.0006249485,0.0001705481,0.002235004,0.0001094144,0.000068965,0.0002185025,0.0002707221,0.7143555,0.01596073,0.03100225,0.001189223,0.2337942],"study_design_scores_gemma":[0.00001650645,0.00003176726,0.0001539506,0.000002816596,0.000009475051,0.00002831211,0.0000161792,0.9942605,0.001813749,0.003281629,0.0003778225,0.000007254527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07026101,0.0006188804,0.9258015,0.0002249083,0.00008241161,0.00006343937,0.00001399909,0.000495807,0.002438],"genre_scores_gemma":[0.9506563,0.0001458274,0.04793277,0.00005047048,0.00007714582,0.00003817975,0.00001783183,0.00001896293,0.001062589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006344072,"threshold_uncertainty_score":0.01261431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002860475749222759,"score_gpt":0.1731364676202069,"score_spread":0.1702759918709841,"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."}}