{"id":"W4234788164","doi":"10.32920/ryerson.14645304.v1","title":"Efficient Resource Management on Container as a Service","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Ontario Stroke Network","funders":"","keywords":"Enforcement; Service-level agreement; Computer science; Scheme (mathematics); Container (type theory); Popularity; Resource management (computing); Resource (disambiguation); Service (business); Business; Computer security; Distributed computing; Computer network; Quality of service; Engineering; Mathematics; Marketing","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":[0.001526937,0.0006636508,0.0007617892,0.0008643389,0.001221396,0.002089959,0.002264732,0.000629674,0.002275339],"category_scores_gemma":[0.003828902,0.0003362694,0.0003953224,0.001298719,0.000908865,0.003083749,0.00205708,0.001169683,0.0008164902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486086,"about_ca_system_score_gemma":0.002809878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007649344,"about_ca_topic_score_gemma":0.005653557,"domain_scores_codex":[0.9975337,0.000594776,0.0001534441,0.0003155803,0.000915112,0.0004874529],"domain_scores_gemma":[0.9975681,0.0003919225,0.0002328195,0.001103851,0.0005056868,0.0001976786],"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":[0.0007986299,0.0004331861,0.003439995,0.0003891506,0.0001266053,0.0008214731,0.0005517626,0.3063716,0.1045636,0.1500861,0.04348525,0.3889327],"study_design_scores_gemma":[0.00003651485,0.00008567608,0.0009276719,0.00002448024,0.00003133741,0.0001562424,0.0001022958,0.946679,0.01606867,0.01515349,0.02069269,0.00004184907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09862605,0.001245743,0.869023,0.001058403,0.0002908005,0.0003331791,0.0001562632,0.009358147,0.01990844],"genre_scores_gemma":[0.7520579,0.000508276,0.2399299,0.0002472149,0.00008840387,0.0001683216,0.0003101105,0.00042923,0.006260673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007649344,"threshold_uncertainty_score":0.01520962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01152272729285905,"score_gpt":0.2437819407515034,"score_spread":0.2322592134586443,"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."}}