{"id":"W2979371912","doi":"10.3390/electronics8101157","title":"High-CMRR Low-Noise Fully Integrated Front-End for EEG Acquisition Systems","year":2019,"lang":"en","type":"article","venue":"Electronics","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Canadian Institutes of Health Research; CMC Microsystems; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Common-mode rejection ratio; Chopper; CMOS; Electronic engineering; Instrumentation amplifier; Amplifier; Electrical engineering; Transistor; Offset (computer science); Input offset voltage; Programmable-gain amplifier; Computer science; Engineering; Operational amplifier; Voltage","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003519546,0.000728931,0.0003940394,0.000339915,0.0002042769,0.0009010432,0.001290112,0.0007917846,0.006002218],"category_scores_gemma":[0.0008077645,0.0003183123,0.0002887812,0.000268125,0.0002314718,0.0009656616,0.000510959,0.0005224882,0.002557593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003180472,"about_ca_system_score_gemma":0.0003065101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004426147,"about_ca_topic_score_gemma":0.00105423,"domain_scores_codex":[0.999431,0.00009314511,0.00002681131,0.0001308936,0.0002684863,0.0000496573],"domain_scores_gemma":[0.9996237,0.0001224737,0.00004093508,0.00004401862,0.0001465184,0.00002224446],"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":[0.0005348863,0.0001119536,0.0008130686,0.0003561596,0.0000708665,0.0003675697,0.0001578355,0.002258674,0.8431287,0.00216144,0.002555412,0.1474833],"study_design_scores_gemma":[0.0002429608,0.002839253,0.009686503,0.0001771785,0.0002378625,0.004092385,0.0001418778,0.1340815,0.800812,0.003276236,0.04425129,0.0001610891],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06906312,0.001100016,0.9170247,0.0003564194,0.0001275992,0.0001718139,0.0003059507,0.005355797,0.006494518],"genre_scores_gemma":[0.677862,0.0005385271,0.3079209,0.0009265132,0.0001793495,0.0001775679,0.0005074051,0.0003589968,0.01152873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006002218,"threshold_uncertainty_score":0.02007943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004318046906175816,"score_gpt":0.1817077032831089,"score_spread":0.1773896563769331,"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."}}