{"id":"W2117513650","doi":"10.1145/502109.502110","title":"Packet delay in models of data networks","year":2001,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Brock University","funders":"","keywords":"Routing table; Computer science; Network packet; Table (database); Routing (electronic design automation); Processing delay; Network delay; End-to-end delay; Computer network; Scalability; Source routing; Routing protocol; Transmission delay; Data mining","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":[0.001030774,0.0009550497,0.0008329835,0.0007824639,0.0007686463,0.001904705,0.001462109,0.001410864,0.002137377],"category_scores_gemma":[0.007464383,0.0006111815,0.0005588812,0.001043722,0.001270247,0.003120906,0.00105493,0.001017038,0.0004054306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002404796,"about_ca_system_score_gemma":0.0009657471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005700369,"about_ca_topic_score_gemma":0.002345214,"domain_scores_codex":[0.9994685,0.0001836126,0.00002056323,0.0001013647,0.0001195849,0.0001063395],"domain_scores_gemma":[0.9969468,0.00214024,0.0003186811,0.0001474223,0.0002685448,0.0001783845],"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":[0.00009627005,0.00003912799,0.0005830241,0.00005822464,0.00001935689,0.00009025503,0.00008479727,0.9178781,0.001054737,0.07723811,0.0009006298,0.001957438],"study_design_scores_gemma":[0.00001639552,0.00003238512,0.00007228423,0.000005644712,0.000009879022,0.00001929103,0.00002181248,0.9739328,0.0002080235,0.02483656,0.0008364173,0.000008357641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.332599,0.003732326,0.6356395,0.002892235,0.000449411,0.00023304,0.001211122,0.0005760412,0.0226673],"genre_scores_gemma":[0.9661973,0.002405794,0.01975974,0.0002586777,0.0001793347,0.0002377866,0.0003187683,0.0001290978,0.01051356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005700369,"threshold_uncertainty_score":0.01744807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08770757930442849,"score_gpt":0.2956826076131928,"score_spread":0.2079750283087643,"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."}}