{"id":"W3217581544","doi":"10.1049/sil2.12080","title":"BCI‐control and monitoring system for smart home automation using wavelet classifiers","year":2021,"lang":"en","type":"article","venue":"IET Signal Processing","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Brain–computer interface; Computer science; Electroencephalography; Artificial intelligence; Wavelet; Pattern recognition (psychology); Feature extraction; Data acquisition; Interface (matter); Signal processing; Speech recognition; Digital signal processing; Computer hardware","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":[0.0002094307,0.0001528191,0.0002073023,0.00007132687,0.0004155278,0.0004556326,0.0001149935,0.00007489596,0.00000197064],"category_scores_gemma":[0.0000627847,0.0001452575,0.00005036143,0.0001876574,0.00005300363,0.0005062952,0.00004180286,0.0001195831,0.000002279597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008408142,"about_ca_system_score_gemma":0.0001137655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003539619,"about_ca_topic_score_gemma":3.828204e-7,"domain_scores_codex":[0.9987177,0.00008280022,0.0002554801,0.0004296254,0.0002173948,0.0002970455],"domain_scores_gemma":[0.9993637,0.0002306253,0.0001400786,0.00009238601,0.00009650918,0.00007673804],"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":[0.00003012581,0.00001823592,0.0005240912,0.0005958445,0.000007263609,0.00002647865,0.0004308128,0.0005784237,0.9678111,0.00008642667,0.00001853758,0.02987264],"study_design_scores_gemma":[0.0005896532,0.00003628623,0.0002836918,0.0005335659,0.00002468543,0.0001233187,0.0004042261,0.4642508,0.5332773,0.0001676539,0.0001372275,0.0001715193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8165994,0.0003067529,0.1819505,0.0001531223,0.0004623873,0.0001771953,0.00001076967,0.0001766113,0.0001631768],"genre_scores_gemma":[0.9944003,0.000002020727,0.005065398,0.0001193874,0.0003084576,0.00001355546,0.000001116209,0.00002295635,0.00006675658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4636724,"threshold_uncertainty_score":0.5923431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04484829437629914,"score_gpt":0.2873429248155279,"score_spread":0.2424946304392287,"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."}}