{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001060772,0.0004875603,0.000885932,0.0002185327,0.0005413214,0.0002087624,0.0003844801,0.0005326772,0.0000135503],"category_scores_gemma":[0.0001013183,0.0004912363,0.0001855278,0.0005330896,0.00007806915,0.0007280992,0.00008751274,0.0005239903,0.00000166553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001549437,"about_ca_system_score_gemma":0.0004451572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000534374,"about_ca_topic_score_gemma":0.00001355932,"domain_scores_codex":[0.9967918,0.0002328271,0.0009858123,0.0009607874,0.0005748073,0.0004539296],"domain_scores_gemma":[0.9977646,0.0001576405,0.0003702052,0.0004482088,0.001138275,0.0001210569],"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":[0.0001659073,0.00006858766,0.001347061,0.004948468,0.0001192527,6.425298e-7,0.03996027,0.9498789,0.000807856,0.0001330223,0.000003146987,0.002566864],"study_design_scores_gemma":[0.0008856085,0.0004714216,0.0001277248,0.001960101,0.0001271283,0.00001257522,0.02873217,0.9640245,0.003149618,0.000003659654,0.00002819581,0.0004773184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5313978,0.001476703,0.4644971,0.00001525288,0.001597814,0.0008834943,0.000003041668,0.00003867742,0.00009008007],"genre_scores_gemma":[0.9899709,0.001353308,0.007207457,0.000006176519,0.0002718518,0.0001655023,0.0002151607,0.00004839107,0.0007612834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.458573,"threshold_uncertainty_score":0.999754,"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."}}