{"id":"W2790464890","doi":"10.1002/spe.2566","title":"Recovering disk storage metrics from low‐level trace events","year":2018,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Tracing; TRACE (psycholinguistics); Computer data storage; Block (permutation group theory); Stateful firewall; Page fault; Key (lock); Object storage; Distributed computing; Virtual memory; Operating system; Memory management","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005642801,0.0009022902,0.000495978,0.002927399,0.0003572107,0.001346437,0.00077566,0.0004380608,0.001064775],"category_scores_gemma":[0.004910328,0.0002028914,0.0002697396,0.001414081,0.0003287807,0.0009007019,0.0007784931,0.0006447109,0.0005654856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007659898,"about_ca_system_score_gemma":0.0006809468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005357507,"about_ca_topic_score_gemma":0.002801912,"domain_scores_codex":[0.9994527,0.0000785051,0.00003832277,0.00007924466,0.0002996927,0.0000516393],"domain_scores_gemma":[0.9978016,0.0006369713,0.000270068,0.0005327003,0.0006221954,0.0001365013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000731328,0.0003747061,0.07274871,0.0003879116,0.0001070441,0.0006165304,0.001061572,0.3618865,0.1185021,0.01207035,0.009166469,0.4223468],"study_design_scores_gemma":[0.00001014887,0.00008142841,0.01036094,0.00001492365,0.00001199379,0.00009321641,0.0001331921,0.939859,0.04355427,0.00403876,0.001815561,0.00002668012],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5295669,0.0002490144,0.4395697,0.0001893264,0.00005287967,0.00009898649,0.001515311,0.02651047,0.002247315],"genre_scores_gemma":[0.9311028,0.00008905393,0.066529,0.00001277614,0.000009662495,0.00005005897,0.001208313,0.0004536188,0.000544725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005357507,"threshold_uncertainty_score":0.01065266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03428704090859698,"score_gpt":0.3070300944455724,"score_spread":0.2727430535369755,"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."}}