{"id":"W2577041194","doi":"10.1109/cloud.2016.0072","title":"Rolling Upgrade with Dynamic Batch Size for IaaS Cloud","year":2016,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); Concordia University","funders":"Amazon Web Services","keywords":"Upgrade; Cloud computing; Downtime; Computer science; Process (computing); Operating system; Pace; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002266487,0.001033408,0.00103673,0.000855037,0.001518011,0.001626476,0.002696065,0.0006584225,0.002688718],"category_scores_gemma":[0.006981761,0.0005330256,0.0007208851,0.0007817723,0.0008422036,0.001982337,0.001539383,0.001543582,0.0008466641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001098108,"about_ca_system_score_gemma":0.002029662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005644469,"about_ca_topic_score_gemma":0.004341077,"domain_scores_codex":[0.9978735,0.0004129622,0.0001553182,0.0005815298,0.0005994657,0.0003772186],"domain_scores_gemma":[0.9959694,0.0009675777,0.000487332,0.001471277,0.0006191947,0.0004852118],"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":[0.002270763,0.0013532,0.01371676,0.0004614104,0.0001654327,0.001056641,0.001121016,0.2537822,0.106269,0.02310163,0.02380277,0.5728992],"study_design_scores_gemma":[0.0001152443,0.0004700382,0.004078351,0.00002509713,0.0000870811,0.0003693675,0.0001834702,0.9624617,0.01516123,0.007530167,0.009431997,0.00008634948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1639563,0.001317302,0.7990168,0.0009395576,0.000774425,0.001114814,0.0003238827,0.02008968,0.01246727],"genre_scores_gemma":[0.8750073,0.0002187851,0.1216692,0.0002315216,0.0001889415,0.0002056672,0.0002220406,0.0002553971,0.002001218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005644469,"threshold_uncertainty_score":0.01198643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00734882984737547,"score_gpt":0.2175660191702343,"score_spread":0.2102171893228588,"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."}}