{"id":"W4391021138","doi":"10.1109/smarttechcon57526.2023.10391528","title":"A Load Balancing Architecture to Improve the Security of Cloud Computing in the Disease Management Centers","year":2023,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Blackberry (Canada)","funders":"","keywords":"Computer science; Cloud computing; Load balancing (electrical power); Provisioning; Scalability; Server; Workload; Round-robin DNS; Distributed computing; Computer network; Reliability (semiconductor); Cloud computing security; Operating system; The Internet; Domain Name 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001447624,0.0005860156,0.0004431502,0.001041269,0.002793032,0.002907882,0.002004176,0.0009715891,0.003800002],"category_scores_gemma":[0.002393683,0.0003378417,0.0004430351,0.0009361869,0.0006605029,0.002971089,0.002136548,0.001116765,0.001571022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002486618,"about_ca_system_score_gemma":0.003623202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008497098,"about_ca_topic_score_gemma":0.00749592,"domain_scores_codex":[0.9989508,0.0002025216,0.00007598253,0.0001980266,0.0003419956,0.0002305914],"domain_scores_gemma":[0.9983256,0.0001444832,0.0001009233,0.0002600819,0.0008412361,0.0003275566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001334898,0.001592118,0.01257528,0.0003104209,0.0001875404,0.0008743522,0.002192652,0.2229076,0.109213,0.1241205,0.07322484,0.4514667],"study_design_scores_gemma":[0.0001740458,0.0003585544,0.004363659,0.00005758373,0.00008921295,0.0002869666,0.0003594221,0.8765438,0.02194712,0.02657354,0.06912289,0.0001232598],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1690511,0.001273028,0.7471724,0.007430785,0.001124647,0.001204269,0.0002390171,0.01383885,0.05866585],"genre_scores_gemma":[0.8441333,0.0003948186,0.1403878,0.0009646038,0.0003622411,0.0002728489,0.0003594682,0.0003592628,0.01276549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008497098,"threshold_uncertainty_score":0.01804173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007276227006477701,"score_gpt":0.2328319958110222,"score_spread":0.2255557688045445,"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."}}