{"id":"W2918686014","doi":"10.1109/ccnc.2019.8651773","title":"A Bee Colony-based Algorithm for Micro-cache Placement Close to End Users in Fog-based Content Delivery Networks","year":2019,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Cache; Server; Latency (audio); Replica; Cloud computing; Computer network; Content delivery; Distributed computing; Quality of service; Operating system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006095349,0.0002654045,0.0003326726,0.0002418802,0.0000850472,0.0001792696,0.0007680333,0.0001142434,0.00003355435],"category_scores_gemma":[0.00001895048,0.0002505368,0.0002013316,0.0003256633,0.00002413864,0.0001831451,0.0001635252,0.0001827309,0.00007030486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002588705,"about_ca_system_score_gemma":0.0001992544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000702646,"about_ca_topic_score_gemma":0.0003086769,"domain_scores_codex":[0.9978848,0.00008899404,0.0003941203,0.0007109091,0.0003134337,0.0006077586],"domain_scores_gemma":[0.9986042,0.000417913,0.00009229407,0.000536503,0.0001559434,0.0001931697],"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":[0.001951359,0.002376014,0.01678341,0.0001647236,0.0003226165,0.0001658639,0.0009869416,0.2796753,0.07011908,0.003853317,0.034358,0.5892434],"study_design_scores_gemma":[0.003983796,0.0006414634,0.0005659543,0.00008379274,0.00001334658,0.00000172526,0.00009414657,0.9874836,0.004029611,0.00001353518,0.002706585,0.0003824086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.274074,0.0001459189,0.7225834,0.001158232,0.000507249,0.001255455,0.00001685015,0.0001319031,0.000127029],"genre_scores_gemma":[0.8774899,0.000005228176,0.1087589,0.0120539,0.00007241272,0.0002717857,0.00002975078,0.00002773861,0.001290376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7078083,"threshold_uncertainty_score":0.9999947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02362267092086749,"score_gpt":0.2324596473140352,"score_spread":0.2088369763931677,"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."}}