{"id":"W2151667449","doi":"10.1109/tmc.2005.19","title":"Call admission control in wideband CDMA cellular networks by using fuzzy logic","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Call blocking; Computer science; Call Admission Control; Code division multiple access; Computer network; Handover; Fuzzy logic; Cellular network; Wideband; Blocking (statistics); Base station; Scheme (mathematics); Telecommunications; Wireless; Wireless network; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007643643,0.000261962,0.000323487,0.0002674307,0.0004867432,0.000206099,0.001281182,0.0001886707,0.00002570011],"category_scores_gemma":[0.000007301897,0.0002681847,0.0001222067,0.0009099319,0.00007601109,0.0003929785,0.00002311528,0.0009446173,0.00002708319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003147392,"about_ca_system_score_gemma":0.00009384734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008176424,"about_ca_topic_score_gemma":0.00003815552,"domain_scores_codex":[0.9972686,0.0004831328,0.0005711608,0.0005846822,0.0004174082,0.0006749723],"domain_scores_gemma":[0.9979427,0.0005998827,0.0001414275,0.0009790079,0.0001088069,0.0002281456],"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":[0.00001475578,0.0002172554,0.00003091068,0.000005522243,0.00001115523,0.000006168317,0.0001332849,0.8330283,0.005084327,0.00003075818,0.0001817669,0.1612557],"study_design_scores_gemma":[0.0009657628,0.00008885767,0.00001157105,0.0001061633,0.000005859973,0.00001177324,0.00001615629,0.9926177,0.00495322,0.00002368772,0.0009357468,0.0002635614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03387071,0.0009421161,0.9635431,0.0004277406,0.000297093,0.0005291578,0.000002384243,0.0002171743,0.000170536],"genre_scores_gemma":[0.9843292,0.00009775163,0.01486213,0.0004412197,0.0001076024,0.00003559489,0.000002429901,0.00002879391,0.00009529076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9504585,"threshold_uncertainty_score":0.9999771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02238673601283529,"score_gpt":0.2845824088462968,"score_spread":0.2621956728334615,"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."}}