{"id":"W2113211994","doi":"10.1109/glocom.2007.961","title":"Admission Control Framework for Delay Bounded Traffic in Cellular Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Handover; Computer science; Admission control; Scheduling (production processes); Computer network; Quality of service; A priori and a posteriori; Bounded function; Cellular network; Interval (graph theory); Real-time computing; Distributed 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":[0.0002402859,0.0001538728,0.0001833154,0.00008659073,0.00004579134,0.00001984254,0.00008980523,0.0002397458,0.00004727312],"category_scores_gemma":[0.00003976724,0.0001559014,0.00004968306,0.0002768709,0.00001332512,0.0001074648,0.000006109653,0.0002121331,0.00000392629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001023106,"about_ca_system_score_gemma":0.000007503817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.388118e-7,"about_ca_topic_score_gemma":0.00003698157,"domain_scores_codex":[0.9990225,0.00001012487,0.0002986673,0.0001655451,0.00007209309,0.000431051],"domain_scores_gemma":[0.999365,0.0003169987,0.0000291552,0.000157056,0.0000274399,0.000104297],"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":[0.00005594069,0.00001548257,0.00008517913,0.00001238093,0.000008780955,0.00000520931,0.00003435901,0.9797842,0.000119636,0.003676201,0.0001843869,0.01601827],"study_design_scores_gemma":[0.0008059643,0.00002494229,0.00007132656,0.00004603647,0.000007103556,0.000001034968,0.00002358594,0.995481,0.0004753426,0.001485476,0.001387226,0.0001910075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02791765,0.0006657211,0.9697585,0.00002393061,0.0004006451,0.0004534254,9.704878e-7,0.0003955075,0.0003836943],"genre_scores_gemma":[0.8581358,0.00005482878,0.1413542,0.0000832779,0.0002238898,0.00002665597,0.00001892285,0.00005300778,0.00004934903],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8302182,"threshold_uncertainty_score":0.6357475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005836397060299586,"score_gpt":0.2274153233451089,"score_spread":0.2215789262848093,"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."}}