{"id":"W4300861755","doi":"10.32920/21262362","title":"Packet-based Adaptive Virtual Channel Configuration for NoC Systems","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Virtual channel; Computer science; Network packet; Router; Computer network; Latency (audio); Queue; Channel (broadcasting); Network on a chip; Throughput; Operating system; Wireless; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003568452,0.0003119825,0.0003168227,0.0004946343,0.0003926732,0.0006640523,0.0009050416,0.0002760487,0.001862038],"category_scores_gemma":[0.0009447958,0.0001465782,0.0001258196,0.000520514,0.0003057737,0.000681816,0.000554114,0.0004088883,0.0002092172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000646653,"about_ca_system_score_gemma":0.0004981518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411265,"about_ca_topic_score_gemma":0.001353641,"domain_scores_codex":[0.9996362,0.00011205,0.00002334409,0.00006028861,0.00009981108,0.00006821367],"domain_scores_gemma":[0.9995047,0.0001462181,0.00004803264,0.0001009682,0.0001569933,0.00004311559],"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":[0.0006101197,0.0001738037,0.00207269,0.0002345069,0.000063019,0.0003277187,0.0001204181,0.5514489,0.06233637,0.0300216,0.009839568,0.3427513],"study_design_scores_gemma":[0.00002371379,0.0001183817,0.000333049,0.00001144729,0.0000160739,0.0001083784,0.00002612002,0.9778561,0.0115777,0.004920195,0.004989011,0.00001974145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1025677,0.001807872,0.8835912,0.0002375626,0.0003828857,0.0001513915,0.0001590618,0.002872773,0.008229465],"genre_scores_gemma":[0.9106984,0.0003592204,0.08575595,0.00008385042,0.0000586339,0.00009435345,0.0001817788,0.00006523206,0.002702599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001862038,"threshold_uncertainty_score":0.006229162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04721709989862587,"score_gpt":0.2656676579024678,"score_spread":0.2184505580038419,"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."}}