{"id":"W2995733890","doi":"10.1109/iemcon.2019.8936243","title":"HMM Optimized Modeling of SSD Storage for I/O MapReduce Workloads","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Workload; Provisioning; Big data; Controller (irrigation); Distributed computing; Real-time computing; Operating system; Embedded system","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":[0.0002467205,0.0003910248,0.0004303413,0.000257536,0.0002802978,0.0005283927,0.0007152297,0.0004106632,0.001343697],"category_scores_gemma":[0.0006960711,0.0002737368,0.0005107815,0.000279913,0.0002342426,0.0005083767,0.0003392666,0.0004514485,0.0002083387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008591044,"about_ca_system_score_gemma":0.001227838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02103048,"about_ca_topic_score_gemma":0.01581945,"domain_scores_codex":[0.9998337,0.00002389133,0.00001170405,0.00004685812,0.00004438579,0.00003952968],"domain_scores_gemma":[0.9997458,0.0001071644,0.00002504955,0.00002587257,0.00007474008,0.00002136114],"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":[0.0000522976,0.00002123082,0.001537497,0.00002405415,0.00001133486,0.00004587072,0.00002789035,0.988915,0.003022255,0.001253893,0.0003738006,0.004714775],"study_design_scores_gemma":[9.805873e-7,0.000003831447,0.0001670015,5.789864e-7,0.000001793108,0.00000338277,0.000003123146,0.999111,0.0003808257,0.000258014,0.00006804091,0.000001499297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4545675,0.0005681,0.5332398,0.0004715458,0.0001290313,0.0001219646,0.001169073,0.001689524,0.008043518],"genre_scores_gemma":[0.9893277,0.0001045773,0.008207873,0.00001896806,0.00001076837,0.00003730485,0.0001960569,0.00003817345,0.002058643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02103048,"threshold_uncertainty_score":0.04181617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02389799030716712,"score_gpt":0.2630725343230122,"score_spread":0.2391745440158451,"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."}}