{"id":"W2936366530","doi":"10.1109/icin.2019.8685875","title":"Optimal Cache Budget Distribution for Hierarchical ICN Networks","year":2019,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Cache; Computer science; Network topology; Computer network; Locality; Information-centric networking; Smart Cache; Cache algorithms; False sharing; Distributed computing; Path (computing); CPU cache","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":[0.0002044978,0.00008012322,0.0001001808,0.00001769956,0.00007146129,0.0001144079,0.0003879988,0.00005746166,0.00001570258],"category_scores_gemma":[0.0000169986,0.00006631226,0.00009206378,0.00009357055,0.00001410456,0.0001891932,0.0001320069,0.0001205003,0.00005708433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002852964,"about_ca_system_score_gemma":0.00002445992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002544082,"about_ca_topic_score_gemma":0.000002366931,"domain_scores_codex":[0.9992399,0.00002578576,0.0001139756,0.0002651129,0.0001151305,0.0002401056],"domain_scores_gemma":[0.9994356,0.0001204162,0.00002482959,0.0003077488,0.00004453754,0.00006689357],"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":[0.0001258916,0.0002078442,0.003716434,0.00002657751,0.00006952842,0.000009161998,0.0001667785,0.05773472,0.00112705,0.7759324,0.06767081,0.09321281],"study_design_scores_gemma":[0.0003284437,0.0001044761,0.000758644,0.000005390925,0.000003196709,0.000007028849,0.000006784981,0.9881498,0.00007700775,0.0003471446,0.01009821,0.0001138814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08379037,0.0000430551,0.9135226,0.0009758429,0.0004775481,0.0001612477,0.00000755963,0.0001454538,0.0008763273],"genre_scores_gemma":[0.9904291,0.000003375199,0.006598328,0.0004158667,0.0001142797,0.00001347711,0.00005410318,0.000004321649,0.002367121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9304151,"threshold_uncertainty_score":0.2704135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009438872937393782,"score_gpt":0.2207814965132174,"score_spread":0.2113426235758236,"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."}}