{"id":"W4280612083","doi":"10.1109/cicc53496.2022.9772782","title":"A SAR-Assisted DC-Coupled Chopper-Stabilized 20μs-Artifact-Recovery $\\Delta \\Sigma$ ADC for Simultaneous Neural Recording and Stimulation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Custom Integrated Circuits Conference (CICC)","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Stimulation; Artifact (error); Brain stimulation; Dynamic range; Delta-sigma modulation; Chopper; Amplifier; Successive approximation ADC; Computer science; SIGNAL (programming language); Neuroscience; Electrical engineering; Capacitor; Artificial intelligence; Bandwidth (computing); Engineering; Voltage; Telecommunications; Psychology; Computer vision","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":[0.0004938848,0.0006634175,0.0004350921,0.0007406849,0.0003582488,0.0005510196,0.001223115,0.0005666299,0.008808536],"category_scores_gemma":[0.000567687,0.0002572759,0.0001809755,0.0006574647,0.0002358575,0.0006327939,0.000539089,0.0008131085,0.005035652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004380595,"about_ca_system_score_gemma":0.0007533496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006116701,"about_ca_topic_score_gemma":0.002166679,"domain_scores_codex":[0.9994891,0.00004099325,0.00002509957,0.0001157488,0.0002963119,0.00003266992],"domain_scores_gemma":[0.9996814,0.00004357523,0.00003210218,0.00005688997,0.0001575908,0.00002857772],"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":[0.0002543494,0.0001262766,0.0004236943,0.0002999687,0.00002917019,0.0002143301,0.00006949607,0.0008863753,0.8164062,0.002554176,0.007909035,0.1708269],"study_design_scores_gemma":[0.00009629299,0.001034411,0.003805164,0.00009491119,0.00008172381,0.003951393,0.00004721614,0.06815868,0.8303954,0.001323807,0.09092136,0.00008959467],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02725628,0.0008851658,0.9491867,0.0003842084,0.0002770256,0.0003936983,0.0006857048,0.007235311,0.0136959],"genre_scores_gemma":[0.3368299,0.0009076935,0.6315984,0.001051993,0.0002337323,0.0004022425,0.00123761,0.0005420949,0.02719634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008808536,"threshold_uncertainty_score":0.02946746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05766483974581644,"score_gpt":0.2770192349817566,"score_spread":0.2193543952359402,"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."}}