{"id":"W2104704160","doi":"10.1109/iembs.2006.260893","title":"Development of a Multi-channel System for Intrinsic Cardiac Neural Recording","year":2006,"lang":"en","type":"article","venue":"","topic":"Atrial Fibrillation Management and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Montréal; Montreal Heart Institute","funders":"","keywords":"Neural activity; Computer science; Neuroscience; Neural system; Nervous system; Channel (broadcasting); Electrophysiology; Artificial neural network; Ablation; Neurophysiology; Artificial intelligence; Medicine; Cardiology; Biology; Telecommunications","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":[0.001606303,0.0005398449,0.0007146053,0.0005900093,0.0005063045,0.0008160096,0.001348346,0.001481412,0.003093382],"category_scores_gemma":[0.002299272,0.0004761057,0.000420461,0.0003264728,0.0005499169,0.001463123,0.001083294,0.001285708,0.001195078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003766858,"about_ca_system_score_gemma":0.0004867676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003160031,"about_ca_topic_score_gemma":0.0007240432,"domain_scores_codex":[0.9987296,0.00024377,0.0001251097,0.0003727913,0.000441757,0.00008698969],"domain_scores_gemma":[0.9984801,0.0005617926,0.0001333399,0.0001890746,0.0005215938,0.0001140715],"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":[0.0002221434,0.0001107565,0.001204089,0.0003961856,0.00006740312,0.0001934962,0.0002405413,0.001216471,0.9003654,0.004644754,0.001043002,0.09029574],"study_design_scores_gemma":[0.0002156411,0.003342889,0.006264872,0.0002649149,0.0003092447,0.004070376,0.0001656795,0.06440018,0.8461218,0.004012302,0.07058274,0.0002493147],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04830548,0.001929144,0.9431271,0.0007209483,0.0003985328,0.000581093,0.0002126728,0.001296139,0.003428817],"genre_scores_gemma":[0.1933553,0.0009173349,0.8008235,0.0005989302,0.0002201457,0.0006619564,0.0001931558,0.0001138352,0.003115796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003093382,"threshold_uncertainty_score":0.01034844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07964243082251886,"score_gpt":0.3147634946519257,"score_spread":0.2351210638294068,"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."}}