{"id":"W4390993506","doi":"10.1109/biocas58349.2023.10388439","title":"Advanced Noise-Shaping SAR ADCs Utilizing Single-Capacitor Arbitrary-Resolution DACs for Miniaturized Neural Interfaces","year":2023,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Successive approximation ADC; Capacitor; Electronic engineering; Noise shaping; Spurious-free dynamic range; Robustness (evolution); Computer science; Effective number of bits; Noise (video); Engineering; Electrical engineering; Voltage; Artificial intelligence; CMOS","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002105032,0.0002753939,0.000306107,0.0002053066,0.0001496585,0.00007971323,0.0002067798,0.0001455005,0.00004526571],"category_scores_gemma":[0.0001016423,0.0002740735,0.0001493697,0.0003658171,0.0000437812,0.0003969165,0.00002622135,0.0002111241,0.00009162886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008821379,"about_ca_system_score_gemma":0.00001603548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006845639,"about_ca_topic_score_gemma":0.00001172466,"domain_scores_codex":[0.9985133,0.00003115241,0.0003629564,0.0003191117,0.0001814795,0.0005919507],"domain_scores_gemma":[0.9993201,0.0002474656,0.00004909971,0.0002075739,0.00005716257,0.0001185858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008370692,0.00002758423,0.00002000133,0.0002621661,0.0001001986,0.00001075859,0.0005106802,0.01174654,0.9519418,0.005827689,0.006449414,0.02301941],"study_design_scores_gemma":[0.00275662,0.0004258304,0.0002269396,0.0003496702,0.0001271938,0.00002129662,0.002394715,0.7331287,0.22749,0.004630927,0.02711951,0.001328583],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6140432,0.001846884,0.3634871,0.00008029415,0.002463731,0.001091538,0.00007675973,0.004363432,0.01254711],"genre_scores_gemma":[0.9968402,0.00005123833,0.001951671,0.0001110412,0.0002461961,0.00004793756,0.00006104564,0.0000816946,0.0006089144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7244518,"threshold_uncertainty_score":0.9999712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06617223081891412,"score_gpt":0.2526765004978638,"score_spread":0.1865042696789497,"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."}}