{"id":"W4390970688","doi":"10.1109/biocas58349.2023.10389106","title":"MEDSA: A Memristive-passive Delta-Sigma ADC Circuit for Detecting Neural Signals","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Successive approximation ADC; Electronic engineering; Delta-sigma modulation; Comparator; Computer science; Memristor; Effective number of bits; Integrator; Noise shaping; Artificial neural network; Control theory (sociology); CMOS; Engineering; Voltage; Artificial intelligence; Electrical engineering; Bandwidth (computing)","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":[0.0001435695,0.0001944795,0.0002209904,0.0001110035,0.0002020956,0.00003039973,0.0001452567,0.00006420918,0.00004475753],"category_scores_gemma":[0.0002032668,0.0001873146,0.0001121987,0.0003980791,0.00001774721,0.0001667976,0.00004896375,0.0001807459,0.00004043659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004144192,"about_ca_system_score_gemma":0.000007839734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002251694,"about_ca_topic_score_gemma":0.000007947935,"domain_scores_codex":[0.9988663,0.00001851519,0.0002511211,0.0002541951,0.0001170355,0.000492832],"domain_scores_gemma":[0.9990465,0.0006216192,0.00003906622,0.0001447327,0.0000516192,0.00009647138],"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":[0.00002655753,0.000008566485,0.00007477162,0.0002008307,0.00008291563,0.00007204066,0.0005079477,0.5722848,0.2599292,0.0005098509,0.001941517,0.1643611],"study_design_scores_gemma":[0.0005173395,0.00009329712,0.0003344903,0.00004431675,0.00002602374,0.00002235034,0.000365371,0.6082567,0.3860958,0.002246012,0.00157868,0.0004195891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6761509,0.0001225147,0.3177342,0.00009392459,0.0007441687,0.0005150774,0.00001770665,0.002761873,0.001859604],"genre_scores_gemma":[0.9983529,0.000007580994,0.0007769463,0.0001048064,0.0002746771,0.00007641697,0.00001063037,0.00005730148,0.0003386856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3222021,"threshold_uncertainty_score":0.7638467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04599086692173299,"score_gpt":0.2727894215698374,"score_spread":0.2267985546481044,"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."}}