{"id":"W2139015629","doi":"10.1109/tbme.2011.2158647","title":"Scalp EEG Acquisition in a Low-Noise Environment: A Quantitative Assessment","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Biotech (Canada); University of British Columbia","funders":"","keywords":"Electroencephalography; Noise (video); Scalp; Energy (signal processing); Laptop; Computer science; Capsule; Artificial intelligence; Frequency band; Pattern recognition (psychology); Acoustics; Mathematics; Statistics; Physics; Telecommunications; Psychology; Medicine; Neuroscience","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":[0.001434364,0.0005993842,0.0003648507,0.0004775952,0.0002331676,0.0005596277,0.0003404492,0.0004395079,0.001841051],"category_scores_gemma":[0.006234295,0.0001588919,0.0002020464,0.0003010113,0.0006551988,0.0005469694,0.0007849846,0.0001913368,0.0003341429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001041465,"about_ca_system_score_gemma":0.0001772444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002672643,"about_ca_topic_score_gemma":0.0003771877,"domain_scores_codex":[0.9990112,0.0004413774,0.00008053856,0.0001451342,0.000262988,0.00005885486],"domain_scores_gemma":[0.9966742,0.001940503,0.0003354712,0.000320899,0.0005398342,0.0001889352],"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":[0.002909538,0.0003254365,0.008039257,0.0005010147,0.00009071032,0.0005605413,0.0007838642,0.001430309,0.9231367,0.0001514238,0.0002079594,0.06186326],"study_design_scores_gemma":[0.0003270837,0.03642192,0.3021515,0.0001018464,0.0005754743,0.008160722,0.001806919,0.01828462,0.6257899,0.0007179305,0.005504147,0.0001578456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9035042,0.0003190268,0.09420183,0.00008436809,0.00003555284,0.000225175,0.0001953246,0.0002500199,0.0011846],"genre_scores_gemma":[0.9665641,0.0003086837,0.03168004,0.00005586361,0.00004612685,0.0001878928,0.000284779,0.0001056839,0.0007667571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001841051,"threshold_uncertainty_score":0.007585764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0240079103215295,"score_gpt":0.2574778884034815,"score_spread":0.233469978081952,"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."}}