{"id":"W4287394597","doi":"","title":"Modeling the Linux page cache for accurate simulation of data-intensive applications","year":2021,"lang":"en","type":"preprint","venue":"Spectrum Research Repository (Concordia University)","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Cache; Bottleneck; Workflow; Cache algorithms; Distributed computing; Key (lock); Parallel computing; Operating system; CPU cache; Database; 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":[0.0006447149,0.000665007,0.0006567164,0.0005941865,0.0007202692,0.001246951,0.001679825,0.001130722,0.002112219],"category_scores_gemma":[0.002922577,0.0003717639,0.0009894416,0.0006807989,0.0006868358,0.001309549,0.0007924345,0.001296731,0.0005193336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001340633,"about_ca_system_score_gemma":0.00287429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03446184,"about_ca_topic_score_gemma":0.01361075,"domain_scores_codex":[0.9995389,0.0001145453,0.00002697883,0.00005600619,0.0001569476,0.0001067683],"domain_scores_gemma":[0.9990563,0.0004151186,0.00009404741,0.0001015453,0.0002444171,0.00008859338],"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":[0.00004003129,0.00005757286,0.002149617,0.00004383987,0.00001215968,0.00004949119,0.00007208602,0.9841375,0.001974214,0.008111147,0.0006229188,0.002729335],"study_design_scores_gemma":[0.000008071956,0.00001144792,0.0001345832,0.000004771814,0.000003675222,0.000005853836,0.000008675891,0.9977918,0.0005240039,0.0006078629,0.0008948229,0.000004510962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4751579,0.001482927,0.4764239,0.001293482,0.0003997846,0.0004762692,0.001727864,0.005473312,0.03756461],"genre_scores_gemma":[0.9059175,0.0009158729,0.08556719,0.000173,0.00005313149,0.0003895122,0.000951581,0.0005361983,0.005495885],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03446184,"threshold_uncertainty_score":0.06852245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1344896973720992,"score_gpt":0.3480933597317742,"score_spread":0.213603662359675,"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."}}