{"id":"W4281775561","doi":"10.1145/3514221.3517834","title":"Proteus: Autonomous Adaptive Storage for Mixed Workloads","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 2022 International Conference on Management of Data","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Online transaction processing; Online analytical processing; Computer science; Workload; Distributed transaction; Transaction processing; Database; Database transaction; Transaction processing system; Operating system; Distributed computing; Data warehouse","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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0008691322,0.0001362179,0.0001599065,0.0001534453,0.0002000755,0.00008774382,0.007959985,0.00001565572,0.00005478459],"category_scores_gemma":[0.00002786493,0.0001146199,0.00008482329,0.0003282044,0.00005303166,0.0001055989,0.01011094,0.0001653897,0.000001892707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009203583,"about_ca_system_score_gemma":0.00002866051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000870833,"about_ca_topic_score_gemma":4.839826e-7,"domain_scores_codex":[0.9980913,0.00001708509,0.0003265438,0.0005267138,0.0008626721,0.0001756364],"domain_scores_gemma":[0.9986655,0.0000405285,0.0004810753,0.0005946519,0.0001917907,0.00002646852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008168839,0.00029403,0.00005863875,0.0001085285,0.0003184892,0.000001176906,0.0002434624,0.001803342,0.0002888821,0.9357973,0.01525304,0.04575146],"study_design_scores_gemma":[0.00101417,0.0005022001,0.001076084,0.0002591386,0.00006902024,0.000003239829,0.003092213,0.914784,0.0006472237,0.02391801,0.0543307,0.0003040633],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2347824,0.0004431228,0.2363595,0.09374557,0.01159751,0.01451393,0.002748931,0.0009039417,0.4049051],"genre_scores_gemma":[0.9751356,0.000009909634,0.01998149,0.0001410835,0.00004941313,0.0001928562,0.00002176743,0.00001137384,0.004456494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9129806,"threshold_uncertainty_score":0.9978951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07251230446442274,"score_gpt":0.2891402640180174,"score_spread":0.2166279595535947,"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."}}