{"id":"W2042968549","doi":"10.1145/2345396.2345436","title":"Advanced adaptive call admission control for mobile cellular networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Call Admission Control; Computer science; Computer network; Handover; Call blocking; Quality of service; Unavailability; Blocking (statistics); Cellular network; Base station; Bandwidth (computing); Voice over IP; Admission control; Call control; Wireless network; Real-time computing; Wireless; Telecommunications; The Internet","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":[0.0006498091,0.0001334882,0.0001782267,0.00005840799,0.0002002239,0.00007026743,0.001325992,0.00009513447,0.00004287508],"category_scores_gemma":[0.00004491688,0.0001109612,0.00008534882,0.0002759593,0.00003991001,0.0006668817,0.0003672589,0.0002078201,0.00003864419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006564951,"about_ca_system_score_gemma":0.00005292301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000777053,"about_ca_topic_score_gemma":0.000003248305,"domain_scores_codex":[0.9984736,0.0001711909,0.0002216392,0.0002499462,0.0002511873,0.0006324233],"domain_scores_gemma":[0.997711,0.000659514,0.00007643175,0.001025746,0.0001933092,0.0003339968],"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":[0.0002356865,0.0006105784,0.0008335177,0.00002085869,0.00008111463,0.000002119667,0.0006692067,0.1738818,0.004570032,0.2073579,0.02354792,0.5881892],"study_design_scores_gemma":[0.0007729437,0.0001396839,0.0001727966,0.00001198738,0.000003003378,0.000001223568,0.00002400407,0.9547988,0.001397397,0.000195517,0.042326,0.00015666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008940491,0.002294465,0.9930577,0.000410149,0.0002331973,0.0009125611,0.000001383627,0.0001854515,0.002011098],"genre_scores_gemma":[0.9126465,0.00006696781,0.08494539,0.0002792272,0.00016661,0.0005065857,0.000005709586,0.00001498962,0.001368053],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9117524,"threshold_uncertainty_score":0.4524867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02393780598523525,"score_gpt":0.2927257652951779,"score_spread":0.2687879593099426,"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."}}