{"id":"W2991477359","doi":"10.1016/j.sysarc.2019.101685","title":"Leveraging partial-refresh for performance and lifetime improvement of 3D NAND flash memory in cyber-physical systems","year":2019,"lang":"en","type":"article","venue":"Journal of Systems Architecture","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University","funders":"National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; National Science Foundation","keywords":"Computer science; Flash (photography); Cyber-physical system; NAND gate; Embedded system; Flash memory; Computer hardware; Operating system; Logic gate; Algorithm","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":[0.00007362447,0.0001516385,0.0001943893,0.000140175,0.0001887175,0.0003594666,0.0004004509,0.0002065867,0.001105924],"category_scores_gemma":[0.0001984241,0.00007227694,0.0001595831,0.0001597202,0.0001514527,0.0005016199,0.0002957351,0.0001315355,0.0001565633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001231696,"about_ca_system_score_gemma":0.0001846685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004542596,"about_ca_topic_score_gemma":0.001459129,"domain_scores_codex":[0.9999561,0.000004818574,0.000003281485,0.000008337151,0.00001598587,0.00001140963],"domain_scores_gemma":[0.9999014,0.00002283589,0.00001136103,0.00002647302,0.00003037559,0.000007551549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004725022,0.0001206616,0.004198826,0.000381569,0.00008165263,0.0006285713,0.0003127512,0.05774067,0.7971386,0.004573741,0.001675398,0.1326751],"study_design_scores_gemma":[0.00003495561,0.0008712334,0.007178134,0.00004100291,0.0001366959,0.0008039423,0.0002701747,0.5151995,0.4627788,0.005005671,0.007622655,0.00005715178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963806,0.002484451,0.02717414,0.0001874092,0.00007346668,0.00001498491,0.0001008758,0.0006460466,0.005512592],"genre_scores_gemma":[0.9976583,0.0001813375,0.001685653,0.0000226647,0.000005528241,0.000003474999,0.00002054147,0.000007182569,0.0004154717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001105924,"threshold_uncertainty_score":0.00369972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008455566641710318,"score_gpt":0.2263710001100935,"score_spread":0.2179154334683832,"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."}}