{"id":"W4415116802","doi":"10.3390/brainsci15101096","title":"Regional Brain Volume Changes Across Adulthood: A Multi-Cohort Study Using MRI Data","year":2025,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Biogen; Eli Lilly and Company; BioClinica; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Eisai; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Brain size; Neuroimaging; Intraclass correlation; Lateral ventricles; Magnetic resonance imaging; Temporal lobe; White matter; Brain morphometry; Brain mapping; Insula","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002950615,0.0004560584,0.0004077511,0.001011816,0.000869003,0.0007655202,0.0004229632,0.000469479,0.0006472517],"category_scores_gemma":[0.002510674,0.0003435254,0.0008517238,0.0007291152,0.0003134975,0.0007166315,0.0009316289,0.0006524278,0.0002205843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002984739,"about_ca_system_score_gemma":0.0003753352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007226405,"about_ca_topic_score_gemma":0.01519655,"domain_scores_codex":[0.9992443,0.0001587786,0.00007483135,0.0003261705,0.0001210518,0.00007485406],"domain_scores_gemma":[0.998652,0.0002027009,0.0003346209,0.0004355281,0.0002423242,0.0001327764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003514626,0.00008709436,0.9923685,0.00002014621,0.0004164382,0.0001896858,0.0007096805,0.0001216721,0.001857345,0.00004543349,0.0002287768,0.003603655],"study_design_scores_gemma":[0.00000942871,0.0001491375,0.9982224,0.000009429402,0.0001375226,0.0003105628,0.0003221133,0.0002655997,0.0002555985,0.00003719892,0.0002719716,0.000008985002],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986922,0.00009790654,0.0005745539,0.00001753296,0.000004038589,0.00002562345,0.0004946837,0.000008395194,0.00008517901],"genre_scores_gemma":[0.9973468,0.0001035826,0.00117143,0.0000209174,0.000008688427,0.00004954487,0.001152145,0.00001491604,0.0001321383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007226405,"threshold_uncertainty_score":0.0156045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2046540247517397,"score_gpt":0.410986695218791,"score_spread":0.2063326704670513,"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."}}