{"id":"W2026061728","doi":"10.1007/s10470-011-9648-z","title":"A new approach to sizing analog CMOS building blocks using pre-compiled neural network models","year":2011,"lang":"en","type":"article","venue":"Analog Integrated Circuits and Signal Processing","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Automation; Electronic design automation; CMOS; Sizing; Electronic engineering; Computer science; Process (computing); Design flow; Amplifier; Engineering; Circuit design; Integrated circuit design; Embedded 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001525023,0.0009615715,0.0004138862,0.0005630184,0.0002995369,0.000866461,0.001044416,0.000290585,0.005139024],"category_scores_gemma":[0.000786497,0.0005020471,0.0005889662,0.0003932258,0.000226891,0.001119502,0.0004099989,0.0008522954,0.0007605039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006314691,"about_ca_system_score_gemma":0.00108128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005158032,"about_ca_topic_score_gemma":0.02419685,"domain_scores_codex":[0.9998525,0.00001990082,0.00001101793,0.00003040492,0.0000692213,0.00001690649],"domain_scores_gemma":[0.9996922,0.0001195188,0.00002707004,0.00006343947,0.00008896847,0.000008833729],"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":[0.0001136735,0.0001120583,0.00089222,0.0002551453,0.0001579493,0.0001495732,0.00009702831,0.5937771,0.04791051,0.01895411,0.00358559,0.333995],"study_design_scores_gemma":[0.00001205485,0.00005087574,0.0001456633,0.0000131207,0.00004312196,0.00004494558,0.00001316605,0.9753999,0.01587182,0.003866449,0.004528353,0.00001060735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01464809,0.0001557434,0.9767393,0.00006205276,0.0000500294,0.00006255985,0.00009543204,0.003040984,0.005145824],"genre_scores_gemma":[0.2464022,0.0001981436,0.7454477,0.00009922845,0.00003232836,0.0001381602,0.0002846666,0.0004721805,0.006925373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005158032,"threshold_uncertainty_score":0.01719177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04723845503049792,"score_gpt":0.24033086170361,"score_spread":0.193092406673112,"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."}}