{"id":"W2112266133","doi":"10.1109/pacrim.2009.5291238","title":"Teaching old caches new tricks: RegionTracker and predictor virtualization","year":2009,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cache; Virtualization; Metadata; Exploit; Operating system; Granularity; Bus sniffing; Cache pollution; Cache algorithms; CPU cache; Parallel computing","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":[],"consensus_categories":[],"category_scores_codex":[0.0001990456,0.00009249272,0.00009529341,0.00009765978,0.0001247634,0.0001646308,0.0002650914,0.00005350676,0.000002982383],"category_scores_gemma":[0.00005871191,0.00007973087,0.00002195907,0.0001573756,0.0000104202,0.0004370454,0.00005027493,0.00008626561,0.0000044409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001587135,"about_ca_system_score_gemma":0.00002839358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009931914,"about_ca_topic_score_gemma":0.000002535507,"domain_scores_codex":[0.9992726,0.00005258165,0.000158487,0.0002488751,0.0001331012,0.0001342914],"domain_scores_gemma":[0.9995453,0.00003931099,0.0000578574,0.0002364465,0.00002892832,0.00009219228],"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":[0.000005887946,0.00007348706,0.001325503,0.0000046637,0.000009050696,0.000004182598,0.002202934,0.001241454,0.0001547321,0.6272817,0.05014542,0.3175509],"study_design_scores_gemma":[0.0005215137,0.000245617,0.006020983,0.00003886624,0.000007067147,0.00003095623,0.00002172226,0.9411737,0.0007200988,0.03686484,0.01403454,0.0003200874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001293172,0.0001134714,0.9895515,0.003075036,0.00004768076,0.00009051699,8.551034e-8,0.00145687,0.00437162],"genre_scores_gemma":[0.5038521,0.00005228414,0.4866907,0.002454001,0.0001289355,0.000001453883,0.000001700312,0.000007317043,0.006811587],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9399322,"threshold_uncertainty_score":0.3251331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542707444414938,"score_gpt":0.2523479555796985,"score_spread":0.2369208811355492,"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."}}