{"id":"W4377091792","doi":"10.3233/shti230114","title":"Low Valence Low Arousal Stimuli: An Effective Candidate for EEG-Based Biometrics Authentication System","year":2023,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Biometrics; Arousal; Valence (chemistry); Computer science; Electroencephalography; Authentication (law); Computer security; Speech recognition; Psychology; 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":[0.0004767983,0.0004646201,0.0004825076,0.0003713527,0.0001700792,0.0005895672,0.0002196041,0.0004122527,0.002179029],"category_scores_gemma":[0.001255616,0.0000956837,0.0003294519,0.0002376407,0.0001794855,0.000409418,0.0003637339,0.0003617042,0.0009478086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198624,"about_ca_system_score_gemma":0.0001390228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002753392,"about_ca_topic_score_gemma":0.0004249375,"domain_scores_codex":[0.9997129,0.00007085929,0.0000193292,0.00006386358,0.00008310466,0.00005003559],"domain_scores_gemma":[0.9997233,0.00008816629,0.00003926765,0.00002414374,0.00009712852,0.00002811374],"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":[0.00284425,0.0005183853,0.0224757,0.0005998675,0.0001335662,0.0004802843,0.0001163858,0.006507949,0.483467,0.000530344,0.003578053,0.4787483],"study_design_scores_gemma":[0.0001736124,0.005308386,0.286238,0.0002800564,0.000453462,0.002779189,0.0004181113,0.3605599,0.3313028,0.001603699,0.01073673,0.0001461826],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8746724,0.003096213,0.111757,0.0006725113,0.0005935226,0.0003070169,0.0006522189,0.001112742,0.007136359],"genre_scores_gemma":[0.9775025,0.0005036679,0.0195513,0.0001764321,0.00008214104,0.00009258743,0.0003383636,0.00002906599,0.001723937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002179029,"threshold_uncertainty_score":0.007289588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05183193575623574,"score_gpt":0.375485707521576,"score_spread":0.3236537717653402,"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."}}