{"id":"W4220804519","doi":"10.7554/elife.66884","title":"Activity in perirhinal and entorhinal cortex predicts perceived visual similarities among category exemplars with highest precision","year":2022,"lang":"en","type":"article","venue":"eLife","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Ontario Trillium Foundation; Fondation Brain Canada","keywords":"Perirhinal cortex; Functional magnetic resonance imaging; Perception; Visual perception; Entorhinal cortex; Temporal cortex; Similarity (geometry); Object (grammar); Temporal lobe","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":[],"consensus_categories":[],"category_scores_codex":[0.0002232602,0.0001478405,0.0001571127,0.0001458583,0.0004319435,0.00007534371,0.0001077241,0.00004707321,0.0008426881],"category_scores_gemma":[0.0000756928,0.0001395329,0.00002736315,0.0001890903,0.0001683411,0.0003807902,0.000115152,0.0003910756,0.00001393466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303557,"about_ca_system_score_gemma":0.000064716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002229453,"about_ca_topic_score_gemma":0.0002331739,"domain_scores_codex":[0.998309,0.0003041923,0.0001438544,0.0004190945,0.000578693,0.0002451656],"domain_scores_gemma":[0.9995737,0.0001229233,0.00006487164,0.0001059686,0.00002249037,0.0001100527],"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":[0.002381556,0.001003696,0.2227055,0.00009044044,0.00000904847,0.0002889183,0.0127551,0.0005453016,0.7469657,0.00005989018,0.001320334,0.01187448],"study_design_scores_gemma":[0.0009417257,0.0005832841,0.9860622,0.0000261086,0.000008085116,0.00008319289,0.001146155,0.004397734,0.005428127,0.00001944415,0.001099861,0.0002040379],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998535,0.00001427237,0.00003288102,0.0002361866,0.0001674554,0.0002732982,0.00004725417,0.00007425906,0.0006193373],"genre_scores_gemma":[0.9989272,0.00009180186,0.00002379807,0.0003306993,0.00004440534,0.00006972801,0.00001513444,0.00001739088,0.0004798733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7633567,"threshold_uncertainty_score":0.9226844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0250043151941341,"score_gpt":0.2676667782884074,"score_spread":0.2426624630942733,"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."}}