{"id":"W2743461105","doi":"10.1109/newcas.2017.8010181","title":"A fully implantable multichip neural interface with a new scalable current-reuse front-end","year":2017,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Electrical engineering; Amplifier; CMOS; Transceiver; Programmable-gain amplifier; Computer science; Low-power electronics; Electromagnetic coil; Electronic engineering; Engineering; Power (physics); Physics; Power consumption","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":[0.0001584497,0.00043228,0.0003667886,0.0003644605,0.000122375,0.0004777061,0.001599276,0.0005381464,0.002726187],"category_scores_gemma":[0.0003030081,0.0001993737,0.0002995024,0.0001988634,0.0001717888,0.0009427372,0.000587331,0.0003407229,0.001243768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002369516,"about_ca_system_score_gemma":0.000253458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001927344,"about_ca_topic_score_gemma":0.0005425406,"domain_scores_codex":[0.9997581,0.00001542347,0.00001644186,0.00005930367,0.0001201274,0.00003064569],"domain_scores_gemma":[0.9998331,0.00002562807,0.00003467445,0.00002662673,0.00006053326,0.00001939696],"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":[0.0001760894,0.000103986,0.0005397983,0.0003777416,0.00005329158,0.0003197926,0.00009206167,0.003829034,0.8091322,0.003120947,0.002281953,0.1799731],"study_design_scores_gemma":[0.0001057654,0.003076833,0.006323851,0.0001132036,0.0002244309,0.004831095,0.00007746419,0.1435165,0.7577265,0.002461345,0.08140653,0.0001364956],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1379622,0.0025227,0.840463,0.0003624565,0.0002349817,0.0001814294,0.0002354283,0.004120262,0.01391753],"genre_scores_gemma":[0.7148454,0.0006612584,0.2698078,0.0005942679,0.0001702445,0.0001361304,0.0002669171,0.0001534206,0.01336465],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002726187,"threshold_uncertainty_score":0.009120047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05116486540945635,"score_gpt":0.3040344900292274,"score_spread":0.252869624619771,"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."}}