{"id":"W4285818748","doi":"10.1109/comst.2022.3191697","title":"Balancing QoS and Security in the Edge: Existing Practices, Challenges, and 6G Opportunities With Machine Learning","year":2022,"lang":"en","type":"article","venue":"IEEE Communications Surveys & Tutorials","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Thunder Bay Regional Research Institute","funders":"","keywords":"Computer science; Provisioning; Quality of service; Computer security; Encryption; Security service; Edge device; Computer network; Cloud computing; Information security","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":[0.005053613,0.000182648,0.0002672594,0.0001567939,0.0007792556,0.0000747335,0.001123566,0.00006007747,0.000005592455],"category_scores_gemma":[0.0006945545,0.0001663333,0.0000156407,0.0002797477,0.0002802943,0.0003295539,0.0006540253,0.001122891,6.812331e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001000496,"about_ca_system_score_gemma":0.00003872613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002710124,"about_ca_topic_score_gemma":0.001418476,"domain_scores_codex":[0.9961616,0.002863073,0.0003604988,0.000185525,0.000212021,0.0002172162],"domain_scores_gemma":[0.9945597,0.003445247,0.000299597,0.001597021,0.00006629136,0.00003216496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001060544,0.0008370507,0.02160554,0.0008910586,0.0005175518,0.00006678999,0.1095708,0.06097266,0.005398883,0.1314834,0.0009945496,0.6675556],"study_design_scores_gemma":[0.002825737,0.0004497452,0.01706808,0.0003445655,0.0001183816,0.0005735395,0.1407674,0.07438751,0.0006835326,0.008423283,0.7523276,0.002030671],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5797094,0.3760902,0.004738539,0.01140275,0.001471576,0.002518604,0.0002480205,0.003331697,0.02048917],"genre_scores_gemma":[0.9428629,0.05452042,0.002050299,0.00001856676,0.00004749201,0.0003780404,0.00006419541,0.0000344569,0.00002363445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7513331,"threshold_uncertainty_score":0.6782876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1519488383419328,"score_gpt":0.3146501242445259,"score_spread":0.1627012859025931,"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."}}