{"id":"W4390202391","doi":"10.2196/54369","title":"Capacity of Generative AI to Interpret Human Emotions From Visual and Textual Data: Pilot Evaluation Study","year":2023,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Mental Health via Writing","field":"Psychology","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mentalization; Psychology; Cognitive psychology; Theory of mind; Comprehension; Cognition; Developmental psychology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007054844,0.001056026,0.000627618,0.0007160164,0.0003806598,0.001632777,0.001412119,0.0008339909,0.004914492],"category_scores_gemma":[0.02460727,0.000348835,0.0007606387,0.0003716697,0.001141305,0.001362416,0.001811195,0.0008740828,0.001368621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006863195,"about_ca_system_score_gemma":0.0006978938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001495746,"about_ca_topic_score_gemma":0.001322469,"domain_scores_codex":[0.9968538,0.001833761,0.000274592,0.0004234206,0.0004177929,0.0001966424],"domain_scores_gemma":[0.979787,0.01432675,0.0006625957,0.001758048,0.002254662,0.001210911],"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":[0.0162921,0.0428605,0.1433059,0.005970124,0.0007619024,0.003037877,0.08198617,0.014583,0.06630745,0.002227248,0.009935896,0.6127319],"study_design_scores_gemma":[0.007071757,0.1418004,0.5238996,0.001155147,0.002269536,0.00549031,0.04056289,0.1443247,0.0801961,0.006954701,0.04551881,0.0007561285],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915859,0.00008051822,0.004158696,0.0000623971,0.00001457412,0.001172513,0.0002659012,0.0002697644,0.002389897],"genre_scores_gemma":[0.9803844,0.0001832257,0.01423173,0.000114468,0.00002158611,0.001948941,0.001005838,0.00007572384,0.002034135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007054844,"threshold_uncertainty_score":0.03731006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2293141211726353,"score_gpt":0.5418588110602662,"score_spread":0.312544689887631,"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."}}