{"id":"W4386242450","doi":"10.1167/jov.23.9.5507","title":"Probing the link between dynamics of “face-selectivity” in macaque IT cortex and facial emotion discrimination behavior","year":2023,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Macaque; Primate; Facial expression; Psychology; Face (sociological concept); Decoding methods; Visual cortex; Convolutional neural network; Pattern recognition (psychology); Computer science; Neuroscience; Artificial intelligence; Cognitive psychology; Communication; Algorithm","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":[0.0003700136,0.0001803705,0.0001475914,0.0001955654,0.0001082737,0.000316268,0.0001727255,0.0002856056,0.0007273788],"category_scores_gemma":[0.002820075,0.0002264765,0.0002593971,0.0001000457,0.0003540647,0.0005558064,0.0003215622,0.0003739332,0.00006663056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003831402,"about_ca_system_score_gemma":0.0001817417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003500561,"about_ca_topic_score_gemma":0.003679038,"domain_scores_codex":[0.9998972,0.0000162772,0.000004534972,0.00003949839,0.0000144366,0.00002801582],"domain_scores_gemma":[0.999574,0.0002169869,0.00008574819,0.00005557516,0.00003061843,0.00003704887],"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":[0.0004422007,0.00009225676,0.116572,0.0001079764,0.0001406038,0.000189033,0.0005389232,0.04486656,0.8051462,0.002641652,0.000211916,0.02905073],"study_design_scores_gemma":[0.00001540482,0.0002446229,0.4488068,0.00001443071,0.00006369046,0.0003319595,0.0001666083,0.4779171,0.06667152,0.005490749,0.0002501645,0.0000269607],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962512,0.00002322029,0.003431863,0.00004191708,0.000001569225,0.000002752193,0.00002863823,0.00001342075,0.0002055146],"genre_scores_gemma":[0.9991785,0.00001410963,0.000683997,0.00001160192,8.601461e-7,0.00000324263,0.00002865398,0.000004247939,0.00007483599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003500561,"threshold_uncertainty_score":0.006960332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05815481004660566,"score_gpt":0.3471329107247614,"score_spread":0.2889781006781558,"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."}}