{"id":"W2054526493","doi":"10.1002/wcm.239","title":"Adaptive admission/congestion control policies for CDMA‐based wireless internet","year":2005,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"King Fahd University of Petroleum and Minerals; Industry Canada; Concordia University","keywords":"Computer science; Computer network; Base station; Time division multiple access; Call Admission Control; Network congestion; Quality of service; Code division multiple access; Air interface; Queueing theory; Admission control; Wireless; CDMA2000; Real-time computing; Wireless network; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009991028,0.0002992343,0.0004090506,0.0002736618,0.0009362819,0.0004096072,0.003703311,0.0001566728,0.000006783607],"category_scores_gemma":[0.00006049556,0.0003013473,0.0001297285,0.000525684,0.0003628601,0.000489358,0.00171606,0.0005039308,0.00001283873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001628433,"about_ca_system_score_gemma":0.000208277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001104681,"about_ca_topic_score_gemma":0.00009323426,"domain_scores_codex":[0.9974394,0.0005247888,0.000638694,0.0005299072,0.0003026086,0.0005646449],"domain_scores_gemma":[0.9937236,0.002249658,0.0003326558,0.002901924,0.0005281753,0.000263956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003852189,0.0003442611,0.0006746415,0.00003533051,0.00005778342,4.741062e-7,0.001547508,0.01145448,0.0006668121,0.09360383,0.0006824713,0.8908939],"study_design_scores_gemma":[0.001229505,0.0001786954,0.0007130865,0.000188903,0.00001369267,0.000008792575,0.0001751932,0.9690084,0.0004112552,0.0001947982,0.02755605,0.0003216459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04970634,0.002733232,0.939308,0.005934731,0.00009031416,0.001255472,0.0000163562,0.0004079835,0.0005475986],"genre_scores_gemma":[0.8942033,0.0004445811,0.1040295,0.0005461812,0.0001109029,0.0004797635,0.00003812082,0.00003385384,0.0001138397],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9575539,"threshold_uncertainty_score":0.9999439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04032257590168921,"score_gpt":0.3228138176755777,"score_spread":0.2824912417738885,"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."}}