{"id":"W2957995827","doi":"10.1109/icc.2019.8761491","title":"Collaborative Content Distribution in 5G Mobile Networks with Edge Caching","year":2019,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Cache; Computer network; Exploit; Enhanced Data Rates for GSM Evolution; Bandwidth (computing); Network topology; Cellular network; Context (archaeology); Core network; Distributed computing; Content distribution; Computer security; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002002741,0.0001018893,0.000141894,0.00003654585,0.00004972045,0.0001220518,0.0002696673,0.00003896809,0.000009410312],"category_scores_gemma":[0.000006685169,0.00007535892,0.00002543077,0.000380226,0.00001602568,0.0003819012,0.00006852137,0.000157286,0.00003549265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009055748,"about_ca_system_score_gemma":0.00005166473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005339614,"about_ca_topic_score_gemma":0.0002586514,"domain_scores_codex":[0.9991575,0.00006359332,0.0001379571,0.0002815311,0.0001454995,0.0002138554],"domain_scores_gemma":[0.9994583,0.00006638349,0.00004900855,0.0002848831,0.0000929526,0.00004849281],"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":[0.0003333581,0.0006447771,0.2248164,0.00003825062,0.0001270756,0.0001526277,0.003077582,0.5459986,0.004441644,0.1590898,0.00439214,0.05688779],"study_design_scores_gemma":[0.001629629,0.0005271994,0.02785165,0.000113551,0.000005686585,0.00001665102,0.00100556,0.9657411,0.0004616302,0.00005664834,0.002187329,0.0004033711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6039694,0.0001676999,0.3927281,0.0001689896,0.0002470343,0.0003176017,0.000003679462,0.00009656275,0.002300928],"genre_scores_gemma":[0.9985632,0.000009878965,0.0002374806,0.0001944194,0.00002255023,0.00002861358,0.00001460259,0.000004142444,0.000925097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4197426,"threshold_uncertainty_score":0.3073048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007483707611125926,"score_gpt":0.1988721865963934,"score_spread":0.1913884789852675,"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."}}