{"id":"W1879969327","doi":"10.1109/icatm.1999.786815","title":"A feasible scheduling algorithm for per-VC queueing ATM switches","year":2003,"lang":"en","type":"article","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Queueing theory; Computer science; Scheduling (production processes); Layered queueing network; Computation; Queueing system; Weighted fair queueing; Computer network; Algorithm; Real-time computing; Distributed computing; Parallel computing; Mathematical optimization; 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":[],"consensus_categories":[],"category_scores_codex":[0.0005111219,0.0001127463,0.0001496783,0.0000596615,0.0002096655,0.0002676366,0.0002827419,0.00006338054,0.00003734538],"category_scores_gemma":[0.00003514207,0.00009440211,0.0001062477,0.0001783308,0.000009534072,0.0003504069,0.00003849408,0.00007363781,0.00004938708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004086965,"about_ca_system_score_gemma":0.00005557889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005512052,"about_ca_topic_score_gemma":0.0000260307,"domain_scores_codex":[0.9990062,0.00003924378,0.0002154733,0.0003167549,0.0001250008,0.0002973581],"domain_scores_gemma":[0.9993768,0.00009585399,0.00005575172,0.0002827613,0.000115645,0.00007321586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003149095,0.00008483227,0.0004777354,0.00003698984,0.00006391677,0.000005230815,0.001060872,0.002551417,0.001008244,0.82068,0.002820646,0.171207],"study_design_scores_gemma":[0.0003491467,0.00007601597,0.00001281607,0.00003288126,0.000003278764,0.0000534564,0.0002407572,0.9589546,0.003911702,0.004349979,0.03181043,0.0002049278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001953029,0.0001560022,0.9831703,0.0002409872,0.001200594,0.0002097876,3.474784e-7,0.000182146,0.01288678],"genre_scores_gemma":[0.4515468,0.000003665441,0.5440726,0.0003296757,0.000193443,0.00004503431,4.574393e-7,0.00001025524,0.003798041],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9564032,"threshold_uncertainty_score":0.3849606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02649184236328101,"score_gpt":0.2579020394017021,"score_spread":0.2314101970384211,"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."}}