{"id":"W4291652749","doi":"10.1109/tim.2022.3194858","title":"A Noncontact Emotion Recognition Method Based on Complexion and Heart Rate","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; Jiangxi Provincial Department of Science and Technology; National Natural Science Foundation of China","keywords":"Emotion recognition; Computer science; Artificial intelligence; Anger; Facial expression; Wearable computer; Speech recognition; Pattern recognition (psychology); Psychology; Social 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":[0.0003561143,0.0006593626,0.0005826842,0.0007227062,0.0001607353,0.0005502084,0.0005652337,0.0004790478,0.003123408],"category_scores_gemma":[0.001015641,0.0001743602,0.000557941,0.0003893295,0.0001836497,0.0009668381,0.0005916643,0.0004567759,0.001240889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001580719,"about_ca_system_score_gemma":0.0001776091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004307201,"about_ca_topic_score_gemma":0.0005877269,"domain_scores_codex":[0.9995227,0.00004898032,0.00003010266,0.0001545206,0.0002004271,0.00004330754],"domain_scores_gemma":[0.9996667,0.00006596738,0.0000510237,0.00004111146,0.0001466894,0.00002853318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004992837,0.0001523497,0.005375202,0.0004000319,0.00009331445,0.0002545817,0.000241982,0.00223084,0.2612678,0.001382255,0.006431033,0.7216713],"study_design_scores_gemma":[0.0001756102,0.001022214,0.10788,0.0001681024,0.0005042187,0.004706079,0.0005058624,0.4993578,0.3481544,0.005138972,0.03204276,0.0003439432],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08107122,0.001102849,0.906844,0.0002617117,0.0004618034,0.0002839716,0.000553201,0.002023957,0.007397245],"genre_scores_gemma":[0.6247026,0.001988434,0.3549242,0.0006179732,0.0004912256,0.0006165557,0.001283646,0.0003778081,0.01499761],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003123408,"threshold_uncertainty_score":0.01044881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1072531132966337,"score_gpt":0.310384985572879,"score_spread":0.2031318722762453,"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."}}