{"id":"W7132973035","doi":"","title":"Inductive Transfer Learning for Incremental Modeling and Optimization of Cloud Systems Performance","year":2021,"lang":"","type":"dissertation","venue":"TSpace","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cloud computing; Testbed; Sampling (signal processing); Reuse; Resource allocation; Performance prediction; Variety (cybernetics); Resource (disambiguation)","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":[0.00161442,0.001234713,0.0007893607,0.0007828765,0.0004632039,0.0009596993,0.001788721,0.0008195689,0.001811926],"category_scores_gemma":[0.007725454,0.0006373245,0.0008526808,0.000802854,0.0008549242,0.001451969,0.001224404,0.002151611,0.0004345561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001864797,"about_ca_system_score_gemma":0.001521441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008692931,"about_ca_topic_score_gemma":0.007945211,"domain_scores_codex":[0.9991959,0.0002973084,0.00003242707,0.0001768562,0.0002075223,0.00009003028],"domain_scores_gemma":[0.9966499,0.002534178,0.0001624204,0.0003010868,0.0002907654,0.00006163766],"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":[0.00002448414,0.00004146879,0.0006021452,0.00002798051,0.00002035286,0.00002318454,0.00002775536,0.9693229,0.0005493643,0.002503331,0.0005413682,0.0263155],"study_design_scores_gemma":[0.000001143721,0.000003651628,0.00002545248,0.000001071086,0.000001225526,0.000001648945,0.000001814478,0.9982161,0.0001780808,0.001502361,0.00006649912,9.547286e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02446885,0.0001774841,0.9719848,0.0001862541,0.00001908261,0.00006488653,0.0001362169,0.001502435,0.001459863],"genre_scores_gemma":[0.7573186,0.0001919632,0.2385418,0.0002032942,0.00005305588,0.0003601447,0.0006779834,0.000264258,0.002389009],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.008692931,"threshold_uncertainty_score":0.01728463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02459811891901831,"score_gpt":0.2905988052697395,"score_spread":0.2660006863507212,"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."}}