{"id":"W1998932429","doi":"10.1002/ett.1279","title":"Novel DLC model for QoS enhancement of bursty VBR traffic in wireless ATM networks","year":2008,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"DOD Prostate Cancer Research Program","keywords":"Variable bitrate; Computer science; Quality of service; Computer network; Wireless; Asynchronous Transfer Mode; Data transmission; Transmission (telecommunications); Constant bitrate; Real-time computing; Telecommunications","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":[0.0003962688,0.000190247,0.0002450614,0.0001804399,0.0004356698,0.00002810503,0.001370483,0.00005290144,0.00001226628],"category_scores_gemma":[0.000008678341,0.0002045019,0.0001635009,0.0005505304,0.0001175974,0.0002180833,0.00002033744,0.0003493128,0.00001597045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006631498,"about_ca_system_score_gemma":0.0001054223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007960662,"about_ca_topic_score_gemma":0.0001090001,"domain_scores_codex":[0.9984537,0.0001873361,0.0005604292,0.000344392,0.0001433955,0.00031073],"domain_scores_gemma":[0.9979672,0.0003256117,0.0001616089,0.001318027,0.0001339451,0.00009362392],"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":[0.00002336163,0.0009059983,0.000004045781,0.000005484957,0.00003165269,7.839719e-7,0.0007417078,0.8025695,0.0002111048,0.003910498,0.000201249,0.1913946],"study_design_scores_gemma":[0.001126198,0.0001066977,0.0002299381,0.00004310981,0.0000156787,0.000008645588,0.00002293913,0.9972413,0.0001520479,0.0000195212,0.0008384695,0.0001954289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009438112,0.0001575343,0.9873006,0.001019511,0.0001592147,0.0005091957,0.00001524534,0.0001586704,0.001241861],"genre_scores_gemma":[0.9275837,0.0006593871,0.07062992,0.0002139856,0.00003225962,0.0001516224,0.0000142014,0.00002705893,0.0006878554],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9181456,"threshold_uncertainty_score":0.8339345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03266858112907921,"score_gpt":0.2385318876509543,"score_spread":0.2058633065218751,"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."}}