{"id":"W4388942832","doi":"10.3390/s23239352","title":"EEG Amplitude Modulation Analysis across Mental Tasks: Towards Improved Active BCIs","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Brain–computer interface; Electroencephalography; Computer science; Binary classification; Support vector machine; Artificial intelligence; Classifier (UML); Brain activity and meditation; Speech recognition; Machine learning; Pattern recognition (psychology); Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001535731,0.0001679748,0.0002207989,0.0001845363,0.0002199995,0.0001390912,0.0002485129,0.00006824196,0.00005690379],"category_scores_gemma":[0.0001286789,0.0001494863,0.0001886369,0.001371896,0.00009030243,0.0001839084,0.0001631108,0.0001303966,0.0002015463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007205644,"about_ca_system_score_gemma":0.00001376181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002168476,"about_ca_topic_score_gemma":0.00006763166,"domain_scores_codex":[0.9984273,0.0001011719,0.0002131619,0.0005479563,0.0003019095,0.0004085375],"domain_scores_gemma":[0.9993541,0.0001324389,0.00009695498,0.0002983678,0.00003486475,0.0000832236],"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":[0.00007892495,0.0000668068,0.0005441074,0.00001158297,0.0001749911,0.00002676094,0.009573688,0.01452949,0.9452165,0.00005347345,0.000651605,0.02907206],"study_design_scores_gemma":[0.0003820761,0.00007946105,0.06272175,0.000007484202,0.00005578542,0.000005696848,0.001138832,0.3873354,0.5460936,0.0001982208,0.001690607,0.0002910845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974949,0.000003207053,0.0002962947,0.0005240827,0.0004164054,0.0001789952,0.000202861,0.0003015399,0.0005816513],"genre_scores_gemma":[0.99762,0.00001256477,0.0001205876,0.0002471656,0.00006302468,0.000009002536,0.00003231137,0.00001703219,0.001878262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3991229,"threshold_uncertainty_score":0.6095876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03369414577481611,"score_gpt":0.3261519026080044,"score_spread":0.2924577568331883,"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."}}