{"id":"W2972263874","doi":"10.1111/cdev.13336","title":"Identifying Liars Through Automatic Decoding of Children's Facial Expressions","year":2019,"lang":"en","type":"article","venue":"Child Development","topic":"Deception detection and forensic psychology","field":"Psychology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Social Sciences and Humanities Research Council of Canada","keywords":"Facial expression; Facial Action Coding System; Psychology; Deception; Surprise; Nonverbal communication; Coding (social sciences); Cognitive psychology; Developmental psychology; Communication; Social psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000823691,0.0002949763,0.0001799918,0.0006418283,0.000168719,0.0003299752,0.0001934314,0.0002063973,0.001101326],"category_scores_gemma":[0.00504727,0.0001360836,0.0001508761,0.0001560124,0.0002314449,0.000506306,0.0004352412,0.0003153708,0.0003087631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002012585,"about_ca_system_score_gemma":0.0002096749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002884494,"about_ca_topic_score_gemma":0.004286284,"domain_scores_codex":[0.9996181,0.0001150937,0.00004095165,0.00007412169,0.00009350078,0.00005817966],"domain_scores_gemma":[0.9983606,0.0004929883,0.0007017865,0.0001243599,0.000268229,0.0000519536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002570979,0.00008123235,0.7746724,0.0001384526,0.00002866793,0.0005247309,0.007102293,0.0003123913,0.08416732,0.000545894,0.0005610219,0.1316084],"study_design_scores_gemma":[0.000008514798,0.0003054504,0.9659217,0.00007831429,0.00003368021,0.001725885,0.004128538,0.002533215,0.02324365,0.0002644688,0.001727968,0.00002855493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962335,0.00009725153,0.002517363,0.00003088831,0.000004768031,0.00001584795,0.000108533,0.00003049348,0.0009613425],"genre_scores_gemma":[0.9960663,0.000169922,0.003207883,0.00001420734,0.000002489098,0.00002422195,0.0001201529,0.000005819448,0.0003889854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002884494,"threshold_uncertainty_score":0.005735457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02986174149482005,"score_gpt":0.3252597784396166,"score_spread":0.2953980369447965,"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."}}