{"id":"W3172943015","doi":"10.1049/ntw2.12029","title":"Performance of cache placement using supervised learning techniques in mobile edge networks","year":2021,"lang":"en","type":"article","venue":"IET Networks","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cache; Enhanced Data Rates for GSM Evolution; Cache algorithms; Computer architecture; Artificial intelligence; Computer network; CPU cache","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00101642,0.000674087,0.0008935883,0.0005100724,0.0003803812,0.0005072044,0.0007669104,0.0007290624,0.0004865257],"category_scores_gemma":[0.003251936,0.0002028964,0.0003246131,0.0005063798,0.0003324698,0.0006391387,0.0004653523,0.0004587469,0.0001370935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001351,"about_ca_system_score_gemma":0.0007286831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009633857,"about_ca_topic_score_gemma":0.0071695,"domain_scores_codex":[0.9994506,0.0002074117,0.00003424874,0.00009701336,0.00009808131,0.0001127224],"domain_scores_gemma":[0.9976239,0.001303779,0.0002785211,0.0001293259,0.0005521465,0.0001122966],"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":[0.0002760792,0.0001891313,0.003301673,0.00003252879,0.00003442807,0.00004254008,0.00002028803,0.9554047,0.001363515,0.0002682454,0.0004801044,0.03858676],"study_design_scores_gemma":[0.000002513229,0.00003766813,0.0001647742,0.000001009271,0.000002034928,0.000004026015,0.000004025232,0.9994069,0.0003045321,0.00005762478,0.00001377451,0.000001005171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8866412,0.0009044367,0.1085196,0.0002629986,0.00007302678,0.00005234231,0.0000924814,0.0009131217,0.00254069],"genre_scores_gemma":[0.9903536,0.0000496286,0.009104077,0.00002797339,0.000007597181,0.00001274912,0.00006813328,0.00000949281,0.0003666377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009633857,"threshold_uncertainty_score":0.01915556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792510850941208,"score_gpt":0.2354074568229134,"score_spread":0.2174823483135013,"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."}}