{"id":"W2989165809","doi":"10.1109/tcc.2019.2953258","title":"Critical Path Analysis through Hierarchical Distributed Virtualized Environments Using Host Kernel Tracing","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Cloud Computing","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Virtualization; Tracing; Virtual machine; TRACE (psycholinguistics); Hypervisor; Host (biology); Distributed computing; Cloud computing; Operating system; Thread (computing); Parallel computing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004129455,0.0005135087,0.0002666525,0.001785669,0.0004458251,0.0006431966,0.000776117,0.0002616589,0.00101241],"category_scores_gemma":[0.001711449,0.0002561173,0.0003164813,0.0007626078,0.0004895509,0.0009629104,0.0008425171,0.0003940783,0.0001581882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006504457,"about_ca_system_score_gemma":0.001367938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006004865,"about_ca_topic_score_gemma":0.005179003,"domain_scores_codex":[0.9996096,0.00007250354,0.00001773224,0.00007812514,0.0001524254,0.00006961748],"domain_scores_gemma":[0.9989372,0.0003801191,0.0001970246,0.0002151654,0.0002048208,0.0000655774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004391516,0.000206167,0.02975317,0.0002097982,0.0001270471,0.0007236134,0.001104819,0.5842382,0.08798284,0.02325354,0.002312686,0.269649],"study_design_scores_gemma":[0.000008400376,0.00004355002,0.001903886,0.000008773931,0.00001474562,0.00008401365,0.00007209689,0.9786261,0.01228213,0.005627858,0.001314878,0.00001365447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1444798,0.0001742932,0.849724,0.0000512791,0.00001353425,0.0000634607,0.0001062253,0.004181969,0.001205446],"genre_scores_gemma":[0.8399702,0.0001180948,0.1584511,0.0000208416,0.000006055269,0.00004532405,0.0001833159,0.0002179041,0.0009872031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006004865,"threshold_uncertainty_score":0.01193982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01759959543129728,"score_gpt":0.2787462953807384,"score_spread":0.2611466999494411,"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."}}