{"id":"W4387870851","doi":"10.1109/icc45041.2023.10279120","title":"Adaptive Service Placement, Task Offloading and Bandwidth Allocation in Task-Oriented URLLC Edge Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Server; Latency (audio); Bandwidth allocation; Computer network; Distributed computing; Bandwidth (computing); Dynamic bandwidth allocation; Enhanced Data Rates for GSM Evolution; Task (project management); Channel allocation schemes; Telecommunications; Wireless; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0005364689,0.0001559875,0.0001569906,0.0002192849,0.0001808523,0.0001244311,0.0003417582,0.00007213139,0.00000249044],"category_scores_gemma":[0.00002150595,0.0001517357,0.00002264311,0.001709221,0.00001826399,0.0004307992,0.000508116,0.0001637166,0.0000657501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006419088,"about_ca_system_score_gemma":0.00004353268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001737152,"about_ca_topic_score_gemma":0.00007524106,"domain_scores_codex":[0.9985938,0.00006815389,0.0002525975,0.0004549238,0.0001781691,0.0004523216],"domain_scores_gemma":[0.9993301,0.0001548941,0.00007146639,0.0002688638,0.00008114595,0.00009354566],"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":[0.0002733745,0.0005562742,0.06507903,0.0003268649,0.0003181518,0.0002473892,0.05613227,0.1582431,0.005575442,0.06696183,0.2457469,0.4005394],"study_design_scores_gemma":[0.0004703763,0.00004776173,0.01060555,0.00005859048,0.000003600356,0.000004164556,0.0001654332,0.9835729,0.00009183478,0.0002602538,0.004525368,0.0001941974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1269989,0.0001505018,0.8616725,0.001293507,0.004573423,0.0003563776,2.769913e-7,0.0006054667,0.004349072],"genre_scores_gemma":[0.9909415,0.00004178867,0.006540605,0.001034774,0.0007341094,0.00002071355,0.00002229938,0.00001755535,0.0006466372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8639426,"threshold_uncertainty_score":0.6187602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01877292317484188,"score_gpt":0.2377063923503494,"score_spread":0.2189334691755075,"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."}}