{"id":"W4311791863","doi":"10.3390/brainsci12121716","title":"Effects of Faces and Voices on the Encoding of Biographic Information","year":2022,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Eye Institute; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Character (mathematics); Perception; Face (sociological concept); Encoding (memory); Matching (statistics); Psychology; Computer science; Communication; Cognitive psychology; Speech recognition; Linguistics; Medicine; Neuroscience","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":[0.0006658791,0.000534435,0.0002883674,0.0001636007,0.0001218239,0.0005421446,0.0002695822,0.0004825907,0.004468685],"category_scores_gemma":[0.00476825,0.0002650751,0.0001704304,0.00006687596,0.0007813788,0.0008403883,0.0005695511,0.0006072914,0.0002054744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001352502,"about_ca_system_score_gemma":0.0001654727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003417396,"about_ca_topic_score_gemma":0.000447726,"domain_scores_codex":[0.9995551,0.0001720364,0.00002750992,0.0001006547,0.00007048095,0.00007412676],"domain_scores_gemma":[0.9953388,0.003660747,0.000328044,0.0002188986,0.0001336282,0.0003198141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0164681,0.001229416,0.005667066,0.0003704449,0.00007508015,0.0002214877,0.00128025,0.0005432051,0.8940964,0.0005477855,0.0001705486,0.0793304],"study_design_scores_gemma":[0.001569768,0.04661727,0.2550743,0.0001887996,0.0006563982,0.001088884,0.002127205,0.01058976,0.6739979,0.004946286,0.002975782,0.0001675971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969625,0.0001248836,0.001065003,0.00003972364,0.00002430528,0.00002062871,0.00002179805,0.00002191414,0.001719066],"genre_scores_gemma":[0.9956727,0.0001609527,0.00245329,0.0001054947,0.00002459621,0.00003199755,0.00003955461,0.0000197584,0.001491687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004468685,"threshold_uncertainty_score":0.0149492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03754715188148981,"score_gpt":0.2731804601945238,"score_spread":0.235633308313034,"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."}}