{"id":"W4315783404","doi":"10.1109/icnsc55942.2022.10004115","title":"Content Placement in a Cluster-Centric Mobile Edge Caching Network","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Concordia University","funders":"","keywords":"Computer science; Computer network; Cache; Enhanced Data Rates for GSM Evolution; Latency (audio); Focus (optics); Distributed computing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003042682,0.0004160538,0.0005399776,0.0006559223,0.0009107261,0.0008688883,0.001179337,0.0008259793,0.0005570106],"category_scores_gemma":[0.0009950356,0.0002737144,0.0002154308,0.001168445,0.0004797038,0.0008066038,0.0006746025,0.0002791936,0.0001964056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001810016,"about_ca_system_score_gemma":0.0009477753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01428613,"about_ca_topic_score_gemma":0.01736474,"domain_scores_codex":[0.9997333,0.00006368607,0.00001132554,0.00006401196,0.0000622134,0.00006551822],"domain_scores_gemma":[0.999433,0.0001640375,0.00007751906,0.00007874815,0.0001826168,0.00006401861],"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":[0.000765086,0.0001484986,0.005436515,0.00009031752,0.00007801927,0.001017416,0.0002501774,0.862408,0.04129342,0.01340377,0.003609644,0.07149918],"study_design_scores_gemma":[0.000009594647,0.00006964724,0.0004232404,0.000004244856,0.0000149982,0.0001321724,0.00006471809,0.9939227,0.003777647,0.001051596,0.0005192294,0.00001021073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5845301,0.0009885,0.4071619,0.0003099268,0.00008286946,0.0001723037,0.0002023902,0.0009045916,0.005647614],"genre_scores_gemma":[0.9588252,0.0001561496,0.03928538,0.00004121099,0.0000136375,0.00002937704,0.00006859279,0.00001323585,0.001567288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01428613,"threshold_uncertainty_score":0.02840596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04485879933440324,"score_gpt":0.2559926914064793,"score_spread":0.2111338920720761,"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."}}