{"id":"W4386473147","doi":"10.1109/tnse.2023.3312369","title":"Intelligent Content Caching and User Association in Mobile Edge Computing Networks for Smart Cities","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Network Science and Engineering","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Western University","funders":"Chongqing Research Program of Basic Research and Frontier Technology","keywords":"Computer science; Latency (audio); Computer network; Association (psychology); Enhanced Data Rates for GSM Evolution; Handover; Frame (networking); Distributed computing; Artificial intelligence; 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":[0.001224089,0.0004545783,0.0008744915,0.0003675461,0.0006827576,0.001042534,0.00110484,0.00101725,0.00048706],"category_scores_gemma":[0.003440878,0.0004210921,0.0004117174,0.001001087,0.0007224118,0.002147316,0.0008855171,0.0007100219,0.00008840217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002247968,"about_ca_system_score_gemma":0.001616935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01481955,"about_ca_topic_score_gemma":0.01586398,"domain_scores_codex":[0.9991264,0.000336999,0.00003457336,0.0001675388,0.0001245015,0.0002100778],"domain_scores_gemma":[0.9987935,0.0006367416,0.0002054218,0.0001168512,0.000156173,0.00009126053],"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":[0.0001334855,0.000106673,0.00371825,0.00004829036,0.00004324875,0.0001491668,0.0001241442,0.9391298,0.005018733,0.01989602,0.0008775785,0.03075457],"study_design_scores_gemma":[0.000003413946,0.00001328492,0.0002050485,0.000001187576,0.000006722635,0.00001536833,0.00002009011,0.9968712,0.0004022009,0.002332517,0.0001248873,0.000004175588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2475789,0.0007591867,0.7493868,0.0005608516,0.0000300056,0.00005868141,0.00004838786,0.0002302078,0.001347013],"genre_scores_gemma":[0.9747679,0.0001859732,0.02430532,0.00004231411,0.00001176085,0.00001796527,0.00002880507,0.00001637745,0.0006236401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01481955,"threshold_uncertainty_score":0.02946663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0219091136189821,"score_gpt":0.2218230306873447,"score_spread":0.1999139170683626,"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."}}