{"id":"W3202684658","doi":"10.15439/2021f91","title":"Design and application of facial expression analysis system in empathy ability of children with autism spectrum disorder","year":2021,"lang":"en","type":"article","venue":"Annals of Computer Science and Information Systems","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Empathy; Autism spectrum disorder; Facial expression; Autism; Psychology; Expression (computer science); Facial expression recognition; Developmental psychology; Intervention (counseling); Cognitive psychology; Facial recognition system; Computer science; Social psychology; Communication; Psychiatry; Pattern recognition (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":[0.0009694061,0.0004494519,0.0003032005,0.0005267682,0.0003099242,0.0003034747,0.0004510227,0.0003516143,0.002942232],"category_scores_gemma":[0.001294692,0.0002061245,0.000403061,0.0001336293,0.000224423,0.0003545546,0.0005072266,0.0002579619,0.0004342762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003665288,"about_ca_system_score_gemma":0.0006520996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119625,"about_ca_topic_score_gemma":0.000986816,"domain_scores_codex":[0.9992272,0.0003141742,0.00005188719,0.0002024945,0.0001200853,0.00008417954],"domain_scores_gemma":[0.9995944,0.0001434209,0.00003537226,0.00002743764,0.0001356321,0.00006375463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003388256,0.003142656,0.09695255,0.0006388081,0.0001086035,0.001167115,0.003616225,0.004863746,0.5600806,0.001418613,0.002468163,0.3221545],"study_design_scores_gemma":[0.001375029,0.01993749,0.4510839,0.0001666476,0.0007406481,0.003138588,0.005565183,0.1318744,0.3685066,0.001819585,0.01547834,0.0003135065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9125339,0.0001167104,0.08069498,0.0002831405,0.00005860949,0.001716839,0.0002857408,0.0007315466,0.003578369],"genre_scores_gemma":[0.9009236,0.000131504,0.09275622,0.0001213652,0.00001769775,0.002960341,0.0002439444,0.00005000058,0.002795311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002942232,"threshold_uncertainty_score":0.009842753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02318281098611272,"score_gpt":0.2833220227903748,"score_spread":0.2601392118042621,"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."}}