{"id":"W4362469108","doi":"10.1038/s41598-023-32244-w","title":"Unfamiliar face matching ability predicts the slope of face learning","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Recall; Face (sociological concept); Psychology; Identity (music); Cognitive psychology; Task (project management); Facial recognition system; Matching (statistics); Identification (biology); Artificial intelligence; Computer science; Pattern recognition (psychology); Mathematics; Biology","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":[0.0008105726,0.0002517308,0.0002266577,0.0004794362,0.00009092795,0.0005625809,0.0001848836,0.0004618779,0.002728181],"category_scores_gemma":[0.007613543,0.0001710937,0.0001948914,0.0001877502,0.0003024772,0.0005988229,0.0003683539,0.0005020612,0.0007781613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000900668,"about_ca_system_score_gemma":0.00007332242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006471016,"about_ca_topic_score_gemma":0.0007525105,"domain_scores_codex":[0.9998098,0.00003057362,0.00002076721,0.00006766044,0.0000435153,0.00002776848],"domain_scores_gemma":[0.9930844,0.002992722,0.001816286,0.001023894,0.0004158981,0.0006667865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007225312,0.000330226,0.9578523,0.00001759173,0.00009586462,0.00006946354,0.0002645335,0.001625691,0.02617407,0.0001642852,0.0001745286,0.01250889],"study_design_scores_gemma":[0.000004558285,0.0002811078,0.9915879,0.000002876279,0.00001402328,0.0002202839,0.00006686997,0.003951824,0.003300665,0.0004460798,0.0001146597,0.000009120792],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984944,0.00003215269,0.0007253515,0.00001104361,0.000002092048,0.000007038022,0.00006460303,0.00001412446,0.0006490313],"genre_scores_gemma":[0.9993006,0.00001769372,0.0003064816,0.000005801347,0.000001570249,0.000004230019,0.0001012425,0.000006343606,0.0002560212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002728181,"threshold_uncertainty_score":0.009126723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04980021317349259,"score_gpt":0.2951448352499995,"score_spread":0.2453446220765069,"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."}}