{"id":"W4295899758","doi":"10.1037/xhp0001046","title":"Don’t look at me like that: Integration of gaze direction and facial expression.","year":2022,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Deutsche Forschungsgemeinschaft","keywords":"Gaze; Psychology; Facial expression; Expression (computer science); Cognitive psychology; Emotional expression; Orientation (vector space); Eye tracking; Communication; Artificial intelligence; Computer science","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":[0.0004704971,0.0002171209,0.0001116088,0.0001749104,0.0002645015,0.0005312005,0.0001063873,0.0003586765,0.004627664],"category_scores_gemma":[0.003862489,0.0001627723,0.000104565,0.0001176512,0.000252199,0.0004532328,0.0002782542,0.0003975235,0.0008179184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002175795,"about_ca_system_score_gemma":0.000135598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00253899,"about_ca_topic_score_gemma":0.005330906,"domain_scores_codex":[0.9998397,0.00005812677,0.000003934906,0.00004376005,0.00003723556,0.00001725114],"domain_scores_gemma":[0.9995029,0.0002144439,0.0001447416,0.00003335483,0.00006221199,0.00004233016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002537098,0.000170493,0.1549457,0.000384264,0.0001749259,0.0008126716,0.008782166,0.0003038996,0.6324406,0.002255216,0.01649751,0.1806955],"study_design_scores_gemma":[0.00005086904,0.0003045301,0.9824071,0.00005394272,0.00007405462,0.0008918685,0.001829474,0.001425777,0.006238648,0.001431369,0.005263024,0.0000294099],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974208,0.001388441,0.002601691,0.001111267,0.0001071046,0.00004110462,0.0004130527,0.00008021773,0.02004908],"genre_scores_gemma":[0.9910864,0.0004321233,0.002352973,0.0005643171,0.00002238214,0.0000458436,0.000255239,0.00003552485,0.005205229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004627664,"threshold_uncertainty_score":0.01548111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07127083197752446,"score_gpt":0.3563045131569045,"score_spread":0.28503368117938,"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."}}