{"id":"W4220842428","doi":"10.3390/s22062346","title":"Automated Feature Extraction on AsMap for Emotion Classification Using EEG","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Feature extraction; Artificial intelligence; Pattern recognition (psychology); Computer science; Electroencephalography; Support vector machine; Convolutional neural network; Differential entropy; Entropy (arrow of time); Feature (linguistics); Speech recognition; Principle of maximum entropy; Rényi entropy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004176226,0.0009063702,0.0005970963,0.001270226,0.0002339879,0.0006679619,0.0004330924,0.0004059705,0.00271104],"category_scores_gemma":[0.001419122,0.0001418244,0.0007714807,0.00112052,0.0001851292,0.000746847,0.0006005884,0.0005246251,0.001202184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000167197,"about_ca_system_score_gemma":0.0003375422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001088045,"about_ca_topic_score_gemma":0.001218197,"domain_scores_codex":[0.9996088,0.00005871287,0.00003690811,0.00008777776,0.000153178,0.00005469589],"domain_scores_gemma":[0.9996659,0.00008966655,0.00004152833,0.00004771233,0.0001419286,0.00001331774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003593224,0.0001458606,0.003711489,0.0002315042,0.00008690155,0.0001932332,0.0000789773,0.007555446,0.1260619,0.0009917662,0.005115736,0.8554678],"study_design_scores_gemma":[0.000084924,0.0007932319,0.09047221,0.0001176252,0.0001623205,0.001389026,0.0003517302,0.6951938,0.1899329,0.005749337,0.01563019,0.0001227035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1106094,0.0006598794,0.8794569,0.0002137452,0.000212217,0.0003557673,0.001752802,0.003539391,0.003199894],"genre_scores_gemma":[0.5964484,0.0007112084,0.3941789,0.0001180518,0.0001377505,0.0007073939,0.003857622,0.0001808772,0.003659846],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00271104,"threshold_uncertainty_score":0.009069264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07217421529605517,"score_gpt":0.3344619873014697,"score_spread":0.2622877720054145,"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."}}