{"id":"W2783335844","doi":"10.1109/icecta.2017.8252002","title":"Sensitivity of reliability of logic gates","year":2017,"lang":"en","type":"article","venue":"2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA)","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Utah Agricultural Experiment Station","keywords":"Logic gate; Reliability (semiconductor); CMOS; Sensitivity (control systems); Computer science; Transistor; Pass transistor logic; Reliability engineering; Electronic engineering; Monte Carlo method; NMOS logic; Logic optimization; Adder; Logic synthesis; Power (physics); Algorithm; Engineering; Mathematics; Electrical engineering","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":[0.001465461,0.0008947222,0.000946465,0.001125239,0.0003392387,0.001084243,0.0009034791,0.001235842,0.00270648],"category_scores_gemma":[0.01359366,0.0006441142,0.001297611,0.0005764475,0.0007724679,0.001340155,0.001286619,0.001096245,0.0004158187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001842878,"about_ca_system_score_gemma":0.0006922623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002213583,"about_ca_topic_score_gemma":0.000930297,"domain_scores_codex":[0.9980861,0.0004785524,0.00006141679,0.0004489935,0.000630551,0.0002943508],"domain_scores_gemma":[0.9945095,0.003846675,0.0004585554,0.0007269573,0.0003550467,0.0001032888],"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":[0.0000833758,0.00002682982,0.001962344,0.00009331424,0.00008530523,0.0001611737,0.00005652508,0.960353,0.01726049,0.01088574,0.0004047032,0.008627368],"study_design_scores_gemma":[0.000006932041,0.0001224274,0.00206693,0.00001991912,0.00004574519,0.0002796234,0.00003229913,0.9715035,0.01026336,0.01462716,0.001004132,0.00002803589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6364626,0.002643644,0.3295137,0.001357927,0.00026788,0.0001323223,0.0009270571,0.001265824,0.02742897],"genre_scores_gemma":[0.9944886,0.0004232505,0.003470446,0.00007404407,0.00002820395,0.00003452872,0.0001292703,0.00006564341,0.00128595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00270648,"threshold_uncertainty_score":0.01337105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02381041412913944,"score_gpt":0.2652626797925017,"score_spread":0.2414522656633623,"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."}}