{"id":"W2148240562","doi":"10.1109/ccece.1998.685643","title":"Adaptive connection admission control for mobile networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Admission control; Homogeneous; Connection (principal bundle); Base station; Computer network; Wireless network; Wireless; Overhead (engineering); Control (management); Distributed computing; Scheme (mathematics); Independence (probability theory); Telecommunications; Engineering; Artificial intelligence","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":[0.0009505479,0.0005770997,0.0005191299,0.0006218188,0.0008071539,0.001046829,0.001279155,0.0008354628,0.001085019],"category_scores_gemma":[0.004099082,0.000205091,0.0002805023,0.0008996676,0.00102503,0.001116852,0.0008288492,0.001400738,0.0003150501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001271314,"about_ca_system_score_gemma":0.001226682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005537136,"about_ca_topic_score_gemma":0.003033046,"domain_scores_codex":[0.9986768,0.0003210183,0.00005442064,0.000173703,0.0006396314,0.0001343878],"domain_scores_gemma":[0.9987017,0.0006078132,0.0001517598,0.0001386036,0.0003295889,0.00007058214],"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":[0.0001877513,0.0001429146,0.0009174365,0.0001885662,0.00009061183,0.0002107765,0.000261071,0.5599464,0.01383928,0.1296618,0.005506278,0.2890471],"study_design_scores_gemma":[0.00002489074,0.00003551655,0.0001361746,0.00001246349,0.00001195378,0.00004492706,0.00001198746,0.9662617,0.001095569,0.02736106,0.004988134,0.00001556173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01794938,0.003117155,0.9710146,0.0007129225,0.0003135705,0.0001066776,0.00003058435,0.001043505,0.005711586],"genre_scores_gemma":[0.9098066,0.002026946,0.08202878,0.0002891932,0.0004736244,0.0002625146,0.00007517461,0.00006549704,0.004971576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005537136,"threshold_uncertainty_score":0.01100981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04178566893527811,"score_gpt":0.2857817980097187,"score_spread":0.2439961290744406,"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."}}