{"id":"W2969463944","doi":"10.1109/tbcas.2019.2936327","title":"A 9.2-g Fully-Flexible Wireless Ambulatory EEG Monitoring and Diagnostics Headband With Analog Motion Artifact Detection and Compensation","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Circuits and Systems","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Computer science; Artifact (error); Wearable computer; Wireless; Bluetooth; Computer hardware; Artificial intelligence; Embedded system; Telecommunications","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":[0.000156174,0.0001722639,0.0002145228,0.0002282129,0.0002608831,0.0001456538,0.00005507575,0.00009570687,0.000003294795],"category_scores_gemma":[0.00001361015,0.0001389608,0.00002050758,0.0003447553,0.000181488,0.0002927463,0.000002022986,0.0002317504,0.000005578094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003336271,"about_ca_system_score_gemma":0.00001505027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005362842,"about_ca_topic_score_gemma":0.000005055298,"domain_scores_codex":[0.9986355,0.00006772407,0.0002212978,0.0004721397,0.0003601215,0.0002432508],"domain_scores_gemma":[0.9993156,0.0002525093,0.00006310581,0.0001357146,0.00002134491,0.0002117369],"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":[0.00002368416,0.00005988976,0.0006742966,0.0001449528,0.000005280245,0.00001377399,0.0001736094,0.0005838093,0.9657546,0.00004379402,8.704674e-7,0.03252149],"study_design_scores_gemma":[0.002455808,0.002240392,0.0458875,0.0006977334,0.00007776594,0.0009522903,0.0005869398,0.1248982,0.8210227,0.00003555054,0.0003600429,0.0007850535],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9403418,0.00007045452,0.05806968,0.00004065041,0.0009793764,0.0003519462,0.00001188931,0.00009521142,0.00003900591],"genre_scores_gemma":[0.999499,0.0003185972,0.000002911673,0.00003123891,0.00004928051,0.00002426188,4.184934e-7,0.00001722501,0.00005703888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1447318,"threshold_uncertainty_score":0.5666658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02809157456944843,"score_gpt":0.240335467721713,"score_spread":0.2122438931522646,"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."}}