{"id":"W4319337184","doi":"10.1088/1741-2552/acb9be","title":"EEG-based detection of modality-specific visual and auditory sensory processing","year":2023,"lang":"en","type":"article","venue":"Journal of Neural Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Electroencephalography; Workload; Modality (human–computer interaction); Task (project management); Brain–computer interface; Sensory processing; Interface (matter); Sensory system; Cognition; Perception; Human–computer interaction; Speech recognition; Artificial intelligence; Cognitive psychology; Psychology; Neuroscience","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":[0.0001699877,0.00009048388,0.0001557355,0.0002481572,0.00004215833,0.00004004676,0.00009343414,0.00003407993,0.000001292463],"category_scores_gemma":[0.0001117043,0.00007839653,0.000056634,0.0002482893,0.00002957006,0.0002247218,0.00002476086,0.000218404,0.000001077258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002037208,"about_ca_system_score_gemma":0.00001396202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.955418e-7,"about_ca_topic_score_gemma":1.147716e-7,"domain_scores_codex":[0.9992133,0.000030715,0.0002820528,0.0001100392,0.0002244019,0.0001394912],"domain_scores_gemma":[0.9994959,0.00018862,0.0001630995,0.00004681437,0.00004831273,0.00005729027],"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":[0.00001963673,0.00001036352,0.00002418009,0.00007577881,0.000001958267,0.00003959951,0.0001035501,0.09601816,0.8924276,0.000003386315,0.00001374504,0.0112621],"study_design_scores_gemma":[0.0001818554,0.0001218564,0.002720066,0.00007388895,0.000003331679,0.00007326012,0.00002778483,0.4511002,0.5453413,0.000006948563,0.0002890427,0.00006052711],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911443,0.000118848,0.007742286,0.0001376328,0.0007631037,0.00003238294,0.000001146673,0.00005312654,0.000007177073],"genre_scores_gemma":[0.9994777,0.00002029058,0.0001871386,0.00002877246,0.0002570045,5.043683e-7,6.462954e-8,0.00001326346,0.00001526522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.355082,"threshold_uncertainty_score":0.3196917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02947985788578165,"score_gpt":0.2695824522406477,"score_spread":0.2401025943548661,"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."}}