{"id":"W3172907266","doi":"10.3389/fnins.2021.667846","title":"Low-Cutoff Frequency Reduction in Neural Amplifiers: Analysis and Implementation in CMOS 65 nm","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Polytechnique Montréal","funders":"","keywords":"Cutoff frequency; CMOS; Amplifier; Transistor; Capacitor; Transconductance; Cutoff; Operational transconductance amplifier; Electrical engineering; Leakage (economics); Low frequency; Electronic engineering; Physics; Materials science; Computer science; Operational amplifier; Engineering; Voltage; Telecommunications","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":[0.0001620183,0.0004532542,0.0002473765,0.0003567635,0.0002409634,0.0004799487,0.0006208207,0.0004830318,0.00265223],"category_scores_gemma":[0.0005782262,0.0001652867,0.000316875,0.0003474995,0.0001476781,0.0005811598,0.0001568317,0.0002803852,0.0005204186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001000223,"about_ca_system_score_gemma":0.0005370795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005238948,"about_ca_topic_score_gemma":0.006827275,"domain_scores_codex":[0.9997434,0.00002910701,0.00001084619,0.00003166697,0.0001384277,0.0000465236],"domain_scores_gemma":[0.999762,0.00008544257,0.00004574057,0.00002340919,0.00007165495,0.00001181135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005564839,0.0003858462,0.00648844,0.0007168208,0.0001835072,0.0007908375,0.0005274148,0.1783073,0.588919,0.02206959,0.003410256,0.1976447],"study_design_scores_gemma":[0.00004790102,0.0006954947,0.003411317,0.00006110937,0.00009288725,0.0003947209,0.0001038084,0.8619966,0.1232092,0.002432365,0.0075255,0.00002914243],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6440639,0.002103736,0.3277943,0.0005816607,0.00008319914,0.000138603,0.0002968582,0.002541393,0.02239616],"genre_scores_gemma":[0.9643993,0.0003757749,0.03169832,0.00004931497,0.00001314534,0.00003635967,0.00006296903,0.00004451006,0.003320417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005238948,"threshold_uncertainty_score":0.01041692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009030168619466023,"score_gpt":0.2373301158457615,"score_spread":0.2282999472262955,"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."}}