{"id":"W4323244354","doi":"10.5220/0011791700003417","title":"Emotion Transformer: Attention Model for Pose-Based Emotion Recognition","year":2023,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Emotion recognition; Computer science; Transformer; Artificial intelligence; Speech recognition; Pattern recognition (psychology); Cognitive psychology; Psychology; Engineering; Voltage","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":[0.0005146143,0.0001762078,0.000159136,0.0004151099,0.0001929587,0.000034659,0.00006901749,0.0002720531,0.001087511],"category_scores_gemma":[0.00003066169,0.0001782879,0.0002461413,0.000407179,0.00003044991,0.0002216802,0.000003527695,0.0001238636,0.002666136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005538394,"about_ca_system_score_gemma":0.00002872604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002036868,"about_ca_topic_score_gemma":0.00002808006,"domain_scores_codex":[0.9985659,0.00009129183,0.0003691642,0.0004160311,0.0001857615,0.0003718947],"domain_scores_gemma":[0.999356,0.00006722299,0.00009776946,0.0001756349,0.0002112904,0.00009204292],"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":[0.0007362916,0.001332372,0.0003845139,0.0002695625,0.0001396565,0.000004473734,0.001830995,0.001409281,0.01960364,0.006170868,0.0657651,0.9023532],"study_design_scores_gemma":[0.009964025,0.001134757,0.02376496,0.0001761723,0.0002617907,0.00002018622,0.002354141,0.91521,0.004488391,0.03962167,0.002098898,0.0009050143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3138876,0.000006078049,0.6591972,0.002031072,0.001528602,0.001057136,0.0001382129,0.0009403738,0.0212137],"genre_scores_gemma":[0.9767126,0.00001882676,0.002318892,0.0007542612,0.0002658916,0.0003565862,0.00480159,0.00005469732,0.01471664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9138007,"threshold_uncertainty_score":0.9998257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1039748828287665,"score_gpt":0.3418316189235818,"score_spread":0.2378567360948153,"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."}}