{"id":"W3130584323","doi":"10.3389/fnins.2021.600543","title":"Optimal Approach for Signal Detection in Steady-State Visual Evoked Potentials in Humans Using Single-Channel EEG and Stereoscopic Stimuli","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; New York University Abu Dhabi; Nvidia; Wellcome Trust; Wellcome","keywords":"Electroencephalography; Computer science; Spectral density; Stereoscopy; Evoked potential; Pattern recognition (psychology); Artificial intelligence; Stimulus (psychology); Visual evoked potentials; SIGNAL (programming language); Channel (broadcasting); Speech recognition; Neuroscience; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001051967,0.0005873702,0.0005440025,0.001233225,0.0002705452,0.001054093,0.0003744853,0.0006748784,0.001242581],"category_scores_gemma":[0.006977682,0.0003349294,0.0003306328,0.0004728677,0.0006076142,0.001050312,0.0006879269,0.0003783893,0.0002703361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005100933,"about_ca_system_score_gemma":0.000724115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001268136,"about_ca_topic_score_gemma":0.001614573,"domain_scores_codex":[0.9991365,0.0002360216,0.00005812258,0.0002322833,0.0002891464,0.00004786987],"domain_scores_gemma":[0.999119,0.0004967813,0.00008681206,0.00006384117,0.0001878625,0.00004571438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001838224,0.0005186556,0.01290479,0.001042799,0.000291608,0.0003961866,0.0007201267,0.1295968,0.3287929,0.02606555,0.001701117,0.4961313],"study_design_scores_gemma":[0.0001214241,0.0009150165,0.02714622,0.000094929,0.0001010296,0.001018652,0.000209527,0.8546582,0.08034778,0.03316474,0.002101194,0.0001213422],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1571357,0.001011521,0.8382699,0.0001813217,0.00005581509,0.0001497263,0.0001644803,0.0004301072,0.002601499],"genre_scores_gemma":[0.6319931,0.0004702101,0.3666531,0.00007530568,0.00003613068,0.0001500334,0.0001102412,0.0001061875,0.0004057746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001268136,"threshold_uncertainty_score":0.005563378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05157986527707291,"score_gpt":0.2795178265922819,"score_spread":0.2279379613152089,"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."}}