{"id":"W2511262144","doi":"10.1109/infcomw.2016.7562226","title":"Mobile-edge computing vs. centralized cloud computing in fiber-wireless access networks","year":2016,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Cloud computing; Computer science; Computer network; Mobile edge computing; Edge computing; Access network; Wireless network; Overhead (engineering); Distributed computing; Wireless broadband; Wireless; Server; Telecommunications; 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":[0.001080281,0.0004280172,0.0005928303,0.0002571021,0.0002758136,0.0006271868,0.002708516,0.0002004679,0.00002487695],"category_scores_gemma":[0.00004603398,0.0003213118,0.0001731474,0.001129247,0.00009750871,0.0008528455,0.002319647,0.0003601452,0.0001373491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001997399,"about_ca_system_score_gemma":0.00009633396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001392128,"about_ca_topic_score_gemma":0.00001113269,"domain_scores_codex":[0.9959461,0.0002739986,0.0008857708,0.001009925,0.0003946103,0.001489586],"domain_scores_gemma":[0.9977255,0.0007706434,0.0002915986,0.0008177396,0.0001321974,0.0002622458],"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":[0.00003855486,0.0002219747,0.05403738,0.00005993611,0.00004508217,0.0001079396,0.001609004,0.006260371,0.0002077161,0.004447566,0.02171365,0.9112508],"study_design_scores_gemma":[0.002282197,0.0001034993,0.01493132,0.0005226191,0.000006839604,0.00003840097,0.00001813844,0.9662042,0.0007243255,0.0004822857,0.01383512,0.0008511052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2881425,0.0001265156,0.696972,0.0003237498,0.008925125,0.0003638526,1.658506e-7,0.000623479,0.004522688],"genre_scores_gemma":[0.9837955,0.00002750469,0.01158742,0.0006226677,0.003222874,0.000005469671,0.000002663344,0.00003888335,0.0006969756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9599438,"threshold_uncertainty_score":0.9999239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193090470763699,"score_gpt":0.2752251496922284,"score_spread":0.2559161026158586,"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."}}