{"id":"W3106623147","doi":"10.1109/ccece47787.2020.9255719","title":"Honeybee Algorithm for Content Delivery Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Computer science; Content delivery; Content (measure theory); Algorithm design; Algorithm; Computer network; Mathematics","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":[0.0003740353,0.0004295218,0.0004208,0.0003691367,0.0003043677,0.0005430192,0.0007314518,0.0005373196,0.001164412],"category_scores_gemma":[0.0007744221,0.0001359123,0.0002640286,0.0003549727,0.0002523929,0.0005066753,0.0002969732,0.0004533181,0.0003178728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003773712,"about_ca_system_score_gemma":0.0003488774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001269348,"about_ca_topic_score_gemma":0.001094319,"domain_scores_codex":[0.9997411,0.00008962525,0.00002130822,0.00003677982,0.0000910126,0.00002002806],"domain_scores_gemma":[0.9997995,0.00007765977,0.00002384754,0.00002334858,0.00006618032,0.000009445543],"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":[0.0002236287,0.000143382,0.001308582,0.0003107575,0.0001491794,0.0001559374,0.0001615562,0.4436389,0.03200015,0.02673434,0.006740004,0.4884336],"study_design_scores_gemma":[0.00004571531,0.00008418394,0.0004274911,0.00001614113,0.00001776645,0.00008934548,0.00002465803,0.9824922,0.004755069,0.004990534,0.007041457,0.00001544889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01466165,0.001882149,0.9788969,0.0001986565,0.000119057,0.0001355973,0.00003589539,0.0007445427,0.003325458],"genre_scores_gemma":[0.3746171,0.001185674,0.6169627,0.0001529596,0.00007001143,0.0006000982,0.0001681466,0.0000928841,0.006150396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001269348,"threshold_uncertainty_score":0.003895342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05742420360498541,"score_gpt":0.2170272424231066,"score_spread":0.1596030388181212,"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."}}