{"id":"W2151679050","doi":"10.1109/iscas.2006.1693056","title":"Electro-Chemical Multi-Channel Integrated Neural Interface Technologies","year":2006,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Interface (matter); Microsystem; Computer science; Brain–computer interface; Amplifier; Dynamic range; Electronic engineering; Electrical engineering; Materials science; CMOS; Engineering; Nanotechnology","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":[0.0006146767,0.0004694258,0.0004469821,0.0008608236,0.0002064083,0.0008998064,0.001363428,0.0006793899,0.002736021],"category_scores_gemma":[0.0006486069,0.0003150642,0.000333071,0.0007422376,0.00020639,0.001115623,0.0004210439,0.0004870338,0.001207315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004531551,"about_ca_system_score_gemma":0.0003181239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002778762,"about_ca_topic_score_gemma":0.0005317955,"domain_scores_codex":[0.9992412,0.00006067007,0.00006230768,0.0001747982,0.0004095524,0.00005144476],"domain_scores_gemma":[0.9996871,0.0001035058,0.0000378737,0.00003129165,0.0001216297,0.00001854809],"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":[0.0002192427,0.0001433215,0.0007069188,0.001856903,0.00006199046,0.0002740471,0.00009615134,0.001916107,0.5494058,0.007035368,0.001823855,0.4364603],"study_design_scores_gemma":[0.00002519507,0.000904339,0.00417878,0.0001422799,0.0001839269,0.003369214,0.00005910396,0.01417816,0.822781,0.001604307,0.1524865,0.00008737358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1362658,0.1765547,0.647149,0.0005911989,0.0007618064,0.0003933804,0.0006191835,0.002562641,0.0351022],"genre_scores_gemma":[0.3668475,0.07010308,0.5237762,0.0007933232,0.0003865856,0.0005368307,0.0009951983,0.0002284368,0.03633278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002736021,"threshold_uncertainty_score":0.009152949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02599380491493779,"score_gpt":0.2569377288098327,"score_spread":0.2309439238948949,"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."}}