{"id":"W2978212785","doi":"10.1016/j.visres.2019.07.007","title":"Part and whole face representations in immediate and long-term memory","year":2019,"lang":"en","type":"article","venue":"Vision Research","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Face (sociological concept); Orientation (vector space); Recognition memory; Cognition; Term (time); Facial recognition system; Encoding (memory); Contrast (vision); Face perception; Communication; Perception; Artificial intelligence; Pattern recognition (psychology); Computer science; Neuroscience; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006448893,0.00005593275,0.00007842348,0.00025805,0.0001109931,0.000108395,0.00007805618,0.00005278745,0.0007952777],"category_scores_gemma":[0.0003180105,0.00004998601,0.00001224725,0.000334444,0.0001445584,0.0002287317,0.0001344521,0.0002623973,0.001091104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001651348,"about_ca_system_score_gemma":0.00002150343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003319638,"about_ca_topic_score_gemma":0.00004607387,"domain_scores_codex":[0.9985784,0.0003375123,0.000121713,0.0003616061,0.0003726703,0.0002281334],"domain_scores_gemma":[0.9992517,0.0004204372,0.00001646987,0.0001720018,0.00003813998,0.0001012314],"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":[0.0000639865,0.00009468254,0.079629,0.00006657415,8.986154e-7,0.00002319037,0.001181464,0.00001020809,0.8654534,0.00006882913,0.001844821,0.051563],"study_design_scores_gemma":[0.001299753,0.0002214891,0.9575772,0.0001261168,0.00000132171,0.00002004151,0.001010405,0.002319272,0.03474905,0.0003414524,0.002181191,0.0001526861],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942422,0.00005882887,0.000007551943,0.001860497,0.00008588617,0.0003759802,0.00001156438,0.00001743379,0.003340056],"genre_scores_gemma":[0.9924357,0.0009675008,0.00001198386,0.0001202418,0.00002200711,0.00001905842,0.000007287824,0.000007632956,0.006408589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8779482,"threshold_uncertainty_score":0.9996867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1346478490207501,"score_gpt":0.4464507957362797,"score_spread":0.3118029467155295,"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."}}