{"id":"W2103437138","doi":"10.1109/ismvl.2002.1011075","title":"Design and implementation of error detection and correction circuitry for multilevel memory protection","year":2003,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Error detection and correction; Reliability (semiconductor); Soft error; Parity bit; Fault tolerance; Code (set theory); Algorithm; Arithmetic; Computer hardware; Parallel computing; Electronic engineering; Distributed computing; Set (abstract data type); Mathematics","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":[0.0004060314,0.00006787791,0.00007752058,0.00008576462,0.0001420088,0.00003732144,0.00003960758,0.00003701074,0.000002776914],"category_scores_gemma":[0.00007499837,0.0000663694,0.00001543708,0.000113125,0.00001599528,0.0003184118,0.00001036632,0.00003997001,3.094559e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002054128,"about_ca_system_score_gemma":0.00002704019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001046344,"about_ca_topic_score_gemma":0.0000297671,"domain_scores_codex":[0.9993994,0.00006001786,0.0001533975,0.0002088894,0.00007035073,0.0001079142],"domain_scores_gemma":[0.999633,0.00008996976,0.00009286316,0.00007948107,0.00007393019,0.00003076473],"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":[6.251439e-7,0.00001067998,0.0002673369,0.00003035118,0.000005574004,1.18866e-7,0.000411938,0.0001340628,0.1103422,0.0003916749,0.000007461731,0.888398],"study_design_scores_gemma":[0.0007729566,0.0003166804,0.008842161,0.00001695526,0.00001285421,0.00007385024,0.0006094732,0.5433909,0.4439487,0.001836078,0.00003355746,0.0001458409],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07966927,0.0000242714,0.9193865,0.00001492625,0.0002181222,0.0005388264,2.758307e-7,0.00006185334,0.00008593292],"genre_scores_gemma":[0.9867239,0.000002737773,0.01311759,0.00002118539,0.00001324985,0.00006856826,3.129006e-7,0.000004664726,0.00004776856],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9070547,"threshold_uncertainty_score":0.2706466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06619536715137363,"score_gpt":0.2945843002550909,"score_spread":0.2283889331037172,"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."}}