{"id":"W2064117904","doi":"10.1145/1601896.1601901","title":"Multichannel intracortical neurorecording","year":2009,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Canada Research Chairs; CMC Microsystems","keywords":"Computer science; Microsystem; Flexibility (engineering); Reliability (semiconductor); Massively parallel; Computer hardware; Brain implant; Embedded system; Wireless; Transducer; Electrode array; Power (physics); Electrical engineering; Voltage; Engineering; Telecommunications; Materials science; Artificial intelligence; Nanotechnology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00004351367,0.0001012872,0.00008553073,0.00006981889,0.00009485966,0.00005594521,0.0002065529,0.00002299797,0.00005706809],"category_scores_gemma":[0.0005201238,0.00008316909,0.00004073469,0.0003021199,0.00003577232,0.0002813674,0.00002611815,0.0001419999,0.0001307476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007896563,"about_ca_system_score_gemma":0.000005956269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.696424e-7,"about_ca_topic_score_gemma":1.238033e-7,"domain_scores_codex":[0.9990379,0.00001941702,0.000114096,0.0003275524,0.0001757347,0.0003253099],"domain_scores_gemma":[0.9996035,0.0001049743,0.00001655302,0.0001482335,0.000006002697,0.0001207387],"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":[0.000004070077,0.00002517285,0.00001095604,7.386131e-7,6.478199e-8,0.00005448751,0.00001190345,0.00008895725,0.9808621,0.008416939,0.00009766148,0.01042696],"study_design_scores_gemma":[0.0001104179,0.0001229924,0.0009762966,0.000002968412,0.000001403156,0.00006863669,0.000004329734,0.04314455,0.9541112,0.0004586587,0.0008772809,0.0001212445],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833384,0.000002409529,0.002691332,0.001697322,0.0005193942,0.00009538518,4.892935e-7,0.0003793651,0.01127587],"genre_scores_gemma":[0.9931107,0.00001134551,0.0002095737,0.006045213,0.00007210604,0.000001804434,5.541715e-8,0.000007087833,0.0005420825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04305559,"threshold_uncertainty_score":0.3391537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03821684331636063,"score_gpt":0.2748739224421218,"score_spread":0.2366570791257611,"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."}}