{"id":"W2898447952","doi":"10.1145/3242102.3242147","title":"Content-centric Edge Caching for 5G Mobile Internet and Beyond","year":2018,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Enhanced Data Rates for GSM Evolution; Computer network; Cellular network; Cellular traffic; Quality of experience; Quality of service; Edge device; The Internet; Mobile edge computing; Core network; Multimedia; Telecommunications; World Wide Web; Cloud computing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001944005,0.00009561014,0.0001131098,0.00007413515,0.0001035904,0.0001880129,0.0003547006,0.00003364311,0.0000135884],"category_scores_gemma":[0.00002981956,0.00007840811,0.00004992978,0.00008715882,0.000046206,0.0002922742,0.0001231963,0.00006081503,0.00003382139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001957259,"about_ca_system_score_gemma":0.00001734687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002382297,"about_ca_topic_score_gemma":0.00004308434,"domain_scores_codex":[0.9992265,0.0000216445,0.0001359322,0.0003036613,0.00009271916,0.0002195876],"domain_scores_gemma":[0.9994672,0.00009408408,0.000038052,0.0002401646,0.00007887148,0.00008161865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001098867,0.0003177841,0.008681748,0.00008120883,0.0001578212,0.0000214897,0.004889954,0.00003088715,0.01843161,0.2052262,0.07176345,0.6902879],"study_design_scores_gemma":[0.00401105,0.002201715,0.002198017,0.00008477753,0.00004472192,0.0001482625,0.0006167601,0.8828032,0.02383137,0.003591259,0.07943527,0.001033613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3594709,0.0004321947,0.6303978,0.0003623069,0.0009046342,0.0003073449,0.000002802984,0.0001948724,0.007927164],"genre_scores_gemma":[0.9919239,0.000008619471,0.002160371,0.001160661,0.0001436319,0.00002454596,0.000001650587,0.000006115753,0.004570518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8827723,"threshold_uncertainty_score":0.319739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02915515923063064,"score_gpt":0.241601454869067,"score_spread":0.2124462956384363,"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."}}