{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002345619,0.0002101194,0.0001888235,0.0001249611,0.0003435705,0.000199409,0.001216834,0.0001111166,0.00002070216],"category_scores_gemma":[0.006263619,0.0002026832,0.00003049622,0.0008172427,0.0002203981,0.006226436,0.001055815,0.0002626079,0.00009508338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008212168,"about_ca_system_score_gemma":0.00005046483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001901589,"about_ca_topic_score_gemma":0.00001553669,"domain_scores_codex":[0.9981788,0.00006073472,0.00023767,0.0007507029,0.0003918267,0.0003802066],"domain_scores_gemma":[0.9975609,0.000881197,0.0002268226,0.001060751,0.0001557568,0.0001146039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009477334,0.0002475781,0.003255804,0.00002579384,0.00004247115,0.0002176063,0.02495092,0.00002508359,0.002480887,0.003217672,0.001029821,0.9644116],"study_design_scores_gemma":[0.003785926,0.002546461,0.0276951,0.0005581444,0.0001645969,0.0007626109,0.04057484,0.02062846,0.1153119,0.09140834,0.6905555,0.006008076],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1573333,0.0009285751,0.8399339,0.0003890356,0.0005716155,0.0001108581,0.00003230674,0.0006085219,0.00009181471],"genre_scores_gemma":[0.5357002,0.0002486429,0.4635402,0.0003525382,0.00006727412,0.00002626856,0.000003293577,0.0000113188,0.00005025269],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9584035,"threshold_uncertainty_score":0.8265181,"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."}}