{"id":"W2111418470","doi":"10.1109/glocom.2009.5426009","title":"Emulation of Optical PIFO Buffers","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Emulation; FIFO and LIFO accounting; Queue; Router; Queueing theory; Network packet; Computer network; Fair queuing; Packet switching; FIFO (computing and electronics); Optical switch; Priority queue; Weighted fair queueing; Speedup; Queuing delay; Distributed computing; Parallel computing; Round-robin scheduling; Dynamic priority scheduling; Quality of service; Computer hardware; Engineering","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":[0.000796006,0.0005783629,0.0002693063,0.0004965066,0.0005334658,0.001030776,0.00198304,0.0006557236,0.00233846],"category_scores_gemma":[0.003197692,0.0002497811,0.0002910172,0.0003405412,0.0006849718,0.001199685,0.0006686262,0.0005783356,0.0002287973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580025,"about_ca_system_score_gemma":0.0008546212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001990746,"about_ca_topic_score_gemma":0.001347245,"domain_scores_codex":[0.9993794,0.0001494313,0.0000376351,0.00009875994,0.0002052974,0.0001294212],"domain_scores_gemma":[0.9980738,0.0009075962,0.0002921901,0.0003008038,0.0003334192,0.00009211185],"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":[0.001568531,0.0003599851,0.003676005,0.0002348335,0.00008299596,0.0005079529,0.0004418362,0.7232137,0.1147027,0.07560278,0.003173247,0.07643541],"study_design_scores_gemma":[0.00005904993,0.0001706365,0.000159577,0.00001069638,0.00001817356,0.00006175162,0.00002804477,0.9375641,0.05432451,0.004291478,0.003297834,0.0000141848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4131023,0.000250172,0.5711157,0.0003449108,0.0002115989,0.000192613,0.000196616,0.003838592,0.01074757],"genre_scores_gemma":[0.8946164,0.0001038862,0.1019777,0.00009858137,0.00002271338,0.0001307341,0.0001132601,0.00009739868,0.002839294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00233846,"threshold_uncertainty_score":0.011464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007471015965994377,"score_gpt":0.2201844451167937,"score_spread":0.2127134291507994,"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."}}