{"id":"W2062291786","doi":"10.1109/mmsp.2012.6343458","title":"Affect recognition using EEG signal","year":2012,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Electroencephalography; Computer science; Categorization; Feature extraction; Pattern recognition (psychology); Artificial intelligence; Emotion classification; Speech recognition; 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002151994,0.00006872476,0.00006593262,0.00007192475,0.00005147514,0.000009439512,0.00002611591,0.00008474683,0.03089889],"category_scores_gemma":[0.000008552966,0.00006158302,0.00005024669,0.00008342849,0.00001701372,0.0001426568,0.000008287307,0.00007710632,0.005146248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001848072,"about_ca_system_score_gemma":0.000004746885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004106693,"about_ca_topic_score_gemma":0.000004250917,"domain_scores_codex":[0.9993958,0.0001084535,0.0001008744,0.0001014298,0.00006612158,0.0002273314],"domain_scores_gemma":[0.9997357,0.00003848976,0.0000359395,0.00007506918,0.0000296343,0.00008518112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001402928,0.001408398,0.01856221,0.00003595341,0.0001805329,0.000009159457,0.00372835,0.000001702772,0.0476311,0.004446453,0.03382571,0.8900301],"study_design_scores_gemma":[0.01300549,0.001522702,0.7630137,0.0003724477,0.0009274815,0.002133596,0.01318578,0.001505602,0.1026749,0.01210304,0.08570686,0.003848399],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6994371,0.0000680667,0.01185908,0.00005433088,0.001178388,0.0001233942,0.000004277463,0.0001134351,0.2871619],"genre_scores_gemma":[0.994957,0.000002059691,0.001767135,0.0005309268,0.0003697061,0.000009051862,0.00003553988,0.00001244642,0.002316106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8861817,"threshold_uncertainty_score":0.9956284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1234024341997585,"score_gpt":0.3659305277006057,"score_spread":0.2425280935008473,"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."}}