{"id":"W2059736581","doi":"10.1109/embc.2014.6944287","title":"A dual slope charge sampling analog front-end for a wireless neural recording system","year":2014,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Sampling (signal processing); Analog signal; Analog front-end; SIGNAL (programming language); Multiplexing; Oversampling; CMOS; Pulse-width modulation; Transmitter; Computer science; Electronic engineering; Channel (broadcasting); Noise (video); Physics; Electrical engineering; Digital signal processing; Voltage; Engineering; Filter (signal processing); Artificial intelligence","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":[0.000403837,0.0002227719,0.0003516419,0.0001085842,0.0001397287,0.00006851793,0.0001412662,0.0001089272,0.00007850606],"category_scores_gemma":[0.00002867429,0.0002077239,0.0001341055,0.00009559397,0.00001633275,0.0001406667,0.00001465342,0.0001436482,0.0001016521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009361179,"about_ca_system_score_gemma":0.00001141696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006968639,"about_ca_topic_score_gemma":0.00004815884,"domain_scores_codex":[0.9987826,0.00003619394,0.0003079541,0.0002636591,0.0001274265,0.0004822154],"domain_scores_gemma":[0.9993841,0.0001891462,0.00003980916,0.0001997756,0.00004994588,0.0001371997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001049143,0.00006525024,0.00155343,0.002585461,0.0006014836,0.00003363131,0.0009968471,0.01835177,0.09108496,0.5948781,0.02654819,0.263196],"study_design_scores_gemma":[0.001580715,0.000233187,0.0003380914,0.0002560077,0.0001456168,0.0000879393,0.0006056562,0.978628,0.004141199,0.001300705,0.01160113,0.001081771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04181123,0.0001542757,0.9387583,0.000008381023,0.0007319196,0.0002939448,0.00001970694,0.0007591982,0.0174631],"genre_scores_gemma":[0.9981251,0.000005697632,0.0005068294,0.00005945767,0.0005402161,0.00007319035,0.00002610251,0.00006514103,0.0005983162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9602762,"threshold_uncertainty_score":0.8470736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02441450174066914,"score_gpt":0.2206894121091842,"score_spread":0.1962749103685151,"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."}}