{"id":"W2105916639","doi":"10.1109/wcnc.2008.356","title":"Statistical Connection Admission Control for Mobile WiMAX Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"WiMAX; Computer science; Computer network; Coding (social sciences); Admission control; Quality of service; Real-time computing; Frame (networking); Connection (principal bundle); Variance (accounting); Wireless; Mathematics; Telecommunications; Statistics","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":[0.001850973,0.000752366,0.0008079442,0.000823478,0.0009184639,0.001310264,0.001295477,0.0005883962,0.0008914379],"category_scores_gemma":[0.009481466,0.0003463862,0.0003202494,0.001275606,0.001278643,0.0009360589,0.0009373527,0.001354851,0.000181974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001770873,"about_ca_system_score_gemma":0.002575956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006892833,"about_ca_topic_score_gemma":0.005330562,"domain_scores_codex":[0.9976013,0.0006759393,0.00009055187,0.0002308951,0.001182384,0.0002190514],"domain_scores_gemma":[0.9956765,0.002603012,0.0005334546,0.0002748031,0.0008003685,0.0001119908],"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":[0.00009895013,0.00006276183,0.0009324712,0.000059995,0.00004347107,0.0000588586,0.00008961157,0.8851311,0.004437776,0.0396226,0.001055591,0.06840686],"study_design_scores_gemma":[0.000004823957,0.00001228822,0.0001119668,0.000002241244,0.000003953551,0.000009093874,0.000003182156,0.9955437,0.0002675819,0.003759366,0.0002771053,0.000004768379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02151668,0.0009421302,0.9743329,0.0003764214,0.0001365283,0.00006697953,0.00002640706,0.0005960797,0.002005906],"genre_scores_gemma":[0.9517158,0.0005138443,0.0459936,0.0001292069,0.0002218172,0.0001741395,0.00004673199,0.00004351217,0.001161405],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006892833,"threshold_uncertainty_score":0.01370543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008590433358699433,"score_gpt":0.2232054443379469,"score_spread":0.2146150109792475,"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."}}