{"id":"W4205197572","doi":"10.3390/electronics11020240","title":"Exploiting Data Compression for Adaptive Block Placement in Hybrid Caches","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; National Research Foundation","keywords":"Static random-access memory; Computer science; Cache; Block (permutation group theory); Latency (audio); Metadata; Embedded system; Parallel computing; Non-volatile memory; Computer hardware; Operating 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003795147,0.0001142878,0.0001362537,0.00010553,0.000248586,0.00003224742,0.002515823,0.00001681602,0.000004239175],"category_scores_gemma":[0.00009538088,0.0001239158,0.00001775816,0.000268502,0.00002251742,0.0005098168,0.003861767,0.0003381507,0.000001921007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004033619,"about_ca_system_score_gemma":0.0001328325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005113795,"about_ca_topic_score_gemma":0.00002946454,"domain_scores_codex":[0.9985505,0.00004711027,0.0001818199,0.0005390227,0.0002335966,0.000447908],"domain_scores_gemma":[0.9985021,0.0001605061,0.0001057008,0.001192684,0.00001777313,0.00002128449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003800873,0.00096426,0.0002230273,0.00006793887,0.0001148496,0.0001968762,0.001796586,0.1793705,0.01691736,0.2577066,0.0789724,0.4632895],"study_design_scores_gemma":[0.0009024509,0.0006458522,0.00001395214,0.00001600414,0.000005619375,0.00003873691,0.0007327907,0.7438002,0.01472944,0.01807626,0.2206876,0.0003511059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01626975,0.003858333,0.977821,0.0007534738,0.0001393249,0.000507829,0.0001469221,0.0004219062,0.00008148214],"genre_scores_gemma":[0.8480277,0.0001175127,0.1510331,0.000191162,0.00002465208,0.0003124767,0.0001991846,0.00001843296,0.00007569997],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.831758,"threshold_uncertainty_score":0.5053139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05817412280470916,"score_gpt":0.2891994388777034,"score_spread":0.2310253160729942,"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."}}