{"id":"W4409494582","doi":"10.1109/taffc.2025.3562027","title":"Partial Label Learning for Emotion Recognition From EEG","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Affective Computing","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Electroencephalography; Emotion recognition; Psychology; Cognitive psychology; Emotion classification; Computer science; Artificial intelligence; Speech recognition; Neuroscience","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":[0.002014732,0.001318303,0.0008015564,0.0007895946,0.000538193,0.001011738,0.001380516,0.001041661,0.001640543],"category_scores_gemma":[0.007434884,0.0002870625,0.001085152,0.0006955396,0.0007789113,0.001802508,0.001636106,0.001836508,0.001063694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005062449,"about_ca_system_score_gemma":0.0006173992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001532362,"about_ca_topic_score_gemma":0.002082084,"domain_scores_codex":[0.9986298,0.0005144862,0.00007651278,0.0004470834,0.0002135387,0.0001185273],"domain_scores_gemma":[0.9974291,0.001176341,0.0002440325,0.0005949012,0.0004558676,0.00009983272],"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":[0.000830756,0.0004359283,0.00568019,0.0002670139,0.0001680474,0.0001164828,0.0004193651,0.08060674,0.02632686,0.003931224,0.006940962,0.8742764],"study_design_scores_gemma":[0.00004484753,0.0001771109,0.001873707,0.00002810488,0.00003981749,0.00006057885,0.00009278209,0.9705285,0.01429112,0.01035654,0.002478759,0.00002801131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07641198,0.0009817649,0.9165359,0.0003517391,0.0001454111,0.0001251195,0.0003222476,0.003337746,0.001788206],"genre_scores_gemma":[0.6832927,0.000488137,0.3088269,0.0004221486,0.000165874,0.0003039606,0.002870247,0.0003144334,0.003315516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002014732,"threshold_uncertainty_score":0.01065505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04141856165419956,"score_gpt":0.3047044322839445,"score_spread":0.263285870629745,"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."}}