{"id":"W4389393863","doi":"10.1101/2023.12.05.23299222","title":"BrainAGE Estimation: Influence of Field Strength, Voxel Size, Race, and Ethnicity","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"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; Pfizer; Novartis Pharmaceuticals Corporation; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Eisai; Alzheimer's Association","keywords":"Ethnic group; Voxel; Neuroimaging; Race (biology); Estimation; Field (mathematics); Stability (learning theory); Statistics; Psychology; Mathematics; Computer science; Artificial intelligence; Biology; Engineering; Machine learning; Neuroscience","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":[0.03172021,0.001195176,0.0009817358,0.0009643087,0.0008257579,0.001697169,0.001502582,0.0007181287,0.003539087],"category_scores_gemma":[0.1075076,0.0004106181,0.00118289,0.001009787,0.001109122,0.001731545,0.001120377,0.001105238,0.0009079636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004872931,"about_ca_system_score_gemma":0.001335824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01750437,"about_ca_topic_score_gemma":0.01330895,"domain_scores_codex":[0.9899087,0.006284122,0.0004453006,0.0021239,0.0008488894,0.0003889478],"domain_scores_gemma":[0.9357712,0.04967043,0.003491123,0.006725787,0.003546706,0.0007947321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00584731,0.0001881333,0.6889632,0.0006710751,0.006280493,0.001102099,0.002752843,0.01708498,0.02068201,0.004259864,0.01277349,0.2393946],"study_design_scores_gemma":[0.0002240856,0.0009101729,0.7955629,0.000346146,0.002656152,0.003059317,0.001337749,0.1423621,0.02553111,0.01269574,0.01509984,0.000214691],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6143724,0.005617901,0.3668602,0.00201437,0.0008157989,0.0002848468,0.00210077,0.003653644,0.004280008],"genre_scores_gemma":[0.9429179,0.0003224325,0.05078769,0.0002859295,0.00007082389,0.0001248201,0.001295489,0.001518394,0.002676473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03172021,"threshold_uncertainty_score":0.1677545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06594420547756673,"score_gpt":0.3812673033361469,"score_spread":0.3153230978585801,"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."}}