{"id":"W2891906560","doi":"10.1109/netsoft.2018.8459970","title":"Dynamic Security Orchestration for CDN Edge-Servers","year":2018,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); University of Waterloo","funders":"","keywords":"Server; Computer science; Computer network; Quality of service; Enhanced Data Rates for GSM Evolution; Overhead (engineering); Orchestration; Cache; Computer security; Operating system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001563726,0.00005470882,0.00005204396,0.00003092507,0.0001006413,0.00009282966,0.0002949193,0.00003064861,0.00001017406],"category_scores_gemma":[0.0000211209,0.00004859192,0.0000473783,0.00008575735,0.00002407022,0.0002901184,0.00005093241,0.00003667509,0.00006071719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000258902,"about_ca_system_score_gemma":0.00003404921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006992602,"about_ca_topic_score_gemma":0.0002106469,"domain_scores_codex":[0.9995043,0.00001443584,0.00008110336,0.0001905659,0.00008192882,0.0001277071],"domain_scores_gemma":[0.9995775,0.00003542379,0.00002402404,0.0002416726,0.00008421117,0.0000371196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008331304,0.0002918676,0.00151908,0.00007524583,0.00008334281,0.000007703216,0.00343095,0.00005941459,0.02274609,0.7913383,0.0438235,0.1365412],"study_design_scores_gemma":[0.0003179202,0.0002169485,0.0007997071,0.000007415193,0.000004477671,0.000004805052,0.00004877615,0.9755666,0.001590884,0.01746607,0.003832763,0.0001436491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1928589,0.00001345882,0.80009,0.0008894493,0.0004856554,0.0001120292,0.000001456354,0.0001853957,0.005363696],"genre_scores_gemma":[0.9893641,0.00000154899,0.008967652,0.0003830863,0.00006158584,0.000007498169,0.000002908112,0.000002806715,0.001208816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9755072,"threshold_uncertainty_score":0.1981521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01718458389869168,"score_gpt":0.2563595333333833,"score_spread":0.2391749494346916,"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."}}