{"id":"W7164128271","doi":"10.31579/2692-9406/233","title":"Quantifying brain atrophy in Frontotemporal Dementia: a head-to-head comparison of neuroimaging techniques*","year":2025,"lang":"","type":"article","venue":"Biomedical Research and Clinical Reviews","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Douglas College; McGill University","funders":"National Institutes of Health; Alliance de recherche numérique du Canada; University of California, San Francisco; University of Southern California","keywords":"Neuroimaging; Atrophy; Grey matter; Frontotemporal dementia; Magnetic resonance imaging; Frontotemporal lobar degeneration; Insula; Brain morphometry","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":[0.007198295,0.001230251,0.0008284647,0.00335699,0.0006189322,0.001251225,0.0005833285,0.0007966001,0.001071246],"category_scores_gemma":[0.01438028,0.0004192982,0.001257543,0.001081561,0.0007850833,0.0006966136,0.001355713,0.0004620512,0.0004337123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003910351,"about_ca_system_score_gemma":0.0004252732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005672882,"about_ca_topic_score_gemma":0.01326738,"domain_scores_codex":[0.9980107,0.0006579185,0.0002312464,0.000517622,0.0004913216,0.00009115562],"domain_scores_gemma":[0.9948643,0.002393032,0.0008144751,0.0007586727,0.001045455,0.0001240071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009843583,0.0004205002,0.4904853,0.002386735,0.01173655,0.0007407523,0.002902437,0.008966194,0.09147032,0.0006909115,0.003759684,0.376597],"study_design_scores_gemma":[0.0001254716,0.002046528,0.9512489,0.0003165623,0.001836584,0.002215561,0.0009985272,0.01850646,0.0175337,0.001548824,0.003462362,0.0001603128],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9647349,0.008315923,0.02229433,0.0001662652,0.0001323587,0.000337869,0.001748858,0.0005870642,0.001682552],"genre_scores_gemma":[0.968298,0.001481432,0.02695169,0.0001391078,0.00008550187,0.0001785414,0.001995654,0.0003024758,0.000567627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007198295,"threshold_uncertainty_score":0.03806865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3483236712595682,"score_gpt":0.6107483086215812,"score_spread":0.262424637362013,"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."}}