{"id":"W2060264247","doi":"10.1109/iscas.2010.5537773","title":"Scaling analysis of yield optimization considering supply and threshold voltage variations","year":2010,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Robustness (evolution); Parametric statistics; Scaling; CMOS; Yield (engineering); Computer science; Integrated circuit; Topology (electrical circuits); Electrical engineering; Mathematics; Engineering; Physics; Statistics; Chemistry","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":[0.0001402403,0.0001002483,0.0001873908,0.0003447316,0.00004832996,0.00003940761,0.00006820298,0.00008288017,0.0005756571],"category_scores_gemma":[0.00004775439,0.00009828143,0.00004275093,0.0005717213,0.00002975512,0.0002433629,0.00002171106,0.000132351,0.000003369747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009336224,"about_ca_system_score_gemma":0.000009574796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004095839,"about_ca_topic_score_gemma":0.000115422,"domain_scores_codex":[0.9994032,0.000002438382,0.0002308409,0.0001204389,0.0001041495,0.000138934],"domain_scores_gemma":[0.9995493,0.0001160341,0.00002937467,0.0002088612,0.00004523587,0.00005125269],"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":[0.000001178811,0.000007544964,0.01378074,0.00001863523,0.0002274889,6.852533e-7,0.0002225925,0.9060108,0.07758613,0.001731158,0.00008483123,0.0003281987],"study_design_scores_gemma":[0.0001015472,0.00000571187,0.005232156,0.000007341848,0.0002354032,0.000001271458,0.00003045589,0.9688567,0.02532974,0.00002949574,0.00005200325,0.0001182124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4328084,0.00003134712,0.5630734,0.00002044997,0.0001741004,0.00008119408,0.000008293338,0.0001714878,0.003631314],"genre_scores_gemma":[0.9656923,0.00003708668,0.03414532,0.00001914411,0.00002494322,0.000006128161,0.00001254757,0.00001684377,0.00004568116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5328839,"threshold_uncertainty_score":0.6303041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008698849107139063,"score_gpt":0.1987233738564796,"score_spread":0.1900245247493405,"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."}}