{"id":"W4387116357","doi":"10.1097/prs.0000000000010667","title":"Artificial Intelligence for Evaluation of Emotions behind Face Masks","year":2023,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Facial expression; Emotional expression; Tribe; Cognitive psychology; Expression (computer science); Face (sociological concept); Psychology; Evolutionary psychology; Theory of mind; Priming (agriculture); Perception; Set (abstract data type); Social psychology; Cognition; Communication; Sociology; 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":[0.001932047,0.0005052186,0.0003208432,0.0008851878,0.0002213324,0.001063452,0.0003812338,0.000731349,0.002915415],"category_scores_gemma":[0.01342779,0.0001488953,0.000429696,0.0005116058,0.0003396965,0.000985581,0.0006091642,0.0006098921,0.000625007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006615357,"about_ca_system_score_gemma":0.000255357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006487636,"about_ca_topic_score_gemma":0.0004933301,"domain_scores_codex":[0.9989324,0.0003536392,0.00006292926,0.0001307758,0.0004704874,0.00004980047],"domain_scores_gemma":[0.9967446,0.002259831,0.0002646146,0.0002267264,0.0004348292,0.00006923988],"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":[0.001811733,0.000482409,0.0420753,0.0003975097,0.0002237172,0.0002973005,0.0003916639,0.0860007,0.0512349,0.03061439,0.007259211,0.7792113],"study_design_scores_gemma":[0.00003816825,0.0004240957,0.02209169,0.00005775332,0.00004081717,0.0002135652,0.000130905,0.9396849,0.0159915,0.01714763,0.004141731,0.0000373743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4987697,0.004646936,0.4501632,0.002207581,0.0006326002,0.0008309783,0.0009738367,0.002320986,0.03945416],"genre_scores_gemma":[0.8637392,0.0004684525,0.1323992,0.0001493032,0.00004283348,0.0002829084,0.0003427069,0.00006053412,0.002514952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002915415,"threshold_uncertainty_score":0.01021773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2257137427960791,"score_gpt":0.3588072728221961,"score_spread":0.133093530026117,"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."}}