{"id":"W2162498183","doi":"10.1109/icc.2005.1494376","title":"Mini round robin: an enhanced frame-based scheduling algorithm for multimedia networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Latency (audio); Quality of service; Scheduling (production processes); Network packet; Computer network; The Internet; Voice over IP; Weighted round robin; Round-robin scheduling; Frame (networking); Real-time computing; Distributed computing; Multimedia; Dynamic priority scheduling; 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":[0.0003338384,0.0002128943,0.0002284968,0.00006656554,0.0001901487,0.0002672255,0.0007258643,0.0001573967,0.00005518118],"category_scores_gemma":[0.00002208017,0.0001974315,0.0001129277,0.0002324367,0.00004147987,0.0006050647,0.00004641286,0.0001761455,0.00004165897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004779978,"about_ca_system_score_gemma":0.00009552645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007110324,"about_ca_topic_score_gemma":0.00003762103,"domain_scores_codex":[0.9983685,0.00005309561,0.0003058323,0.0005553674,0.0002012004,0.000516003],"domain_scores_gemma":[0.9986484,0.0003481304,0.00009532546,0.0005283644,0.0001436998,0.0002360738],"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":[0.000007879167,0.00007959709,0.000003620245,0.000001255154,0.00001133016,8.133528e-7,0.00005010207,0.1958692,0.00006257812,0.001790466,0.0002677584,0.8018554],"study_design_scores_gemma":[0.001540608,0.0001423896,0.00002211559,0.00001422688,0.00001050854,0.000001486399,0.00001650434,0.9917671,0.0007967322,0.00009173882,0.005320697,0.0002759078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001536551,0.0002219484,0.9949226,0.001410096,0.0006706531,0.0004298823,0.000001677609,0.0005256045,0.0002809314],"genre_scores_gemma":[0.3725977,0.000004148623,0.6240798,0.001921033,0.0008831869,0.00008891118,0.0000107993,0.00001286812,0.0004015396],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8015795,"threshold_uncertainty_score":0.8051022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204849975160634,"score_gpt":0.2476309304869226,"score_spread":0.2355824307353162,"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."}}