{"id":"W4417041517","doi":"10.1093/braincomms/fcaf475","title":"Investigating links between white matter hyperintensities and menopausal status using robust age-correction methods in UK Biobank","year":2025,"lang":"en","type":"article","venue":"Brain Communications","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières; McGill University Health Centre; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Menopause; Biobank; Postmenopausal women; Hyperintensity; Blood pressure; Risk factor; Epidemiology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008386378,0.000110374,0.0002154154,0.000355455,0.0002404158,0.00007726945,0.0001472506,0.00009913524,0.00005861142],"category_scores_gemma":[0.0005638058,0.0001112685,0.00002395104,0.0004851467,0.0003177871,0.00009175411,0.0004132355,0.0006160688,0.000005661662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001183892,"about_ca_system_score_gemma":0.0001594267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006674943,"about_ca_topic_score_gemma":0.0002285648,"domain_scores_codex":[0.9986369,0.0004958481,0.0002891947,0.0001858101,0.0001105382,0.000281693],"domain_scores_gemma":[0.9984543,0.0007248502,0.00005398253,0.0005605145,0.0001217331,0.00008461875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009415861,0.0000495301,0.9726481,0.00004570808,0.00006424967,0.000001655179,0.0008362362,0.000008019709,0.008281766,0.0001367686,0.001034351,0.01688416],"study_design_scores_gemma":[0.000621899,0.0000699529,0.9871165,0.0003595645,0.00008428039,0.000009755862,0.002421326,0.004819845,0.0006912728,0.0008065619,0.002897173,0.0001018704],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9398952,0.0006266531,0.01721239,0.02110969,0.0001040237,0.000633536,0.00001033398,0.0000577064,0.02035043],"genre_scores_gemma":[0.892571,0.0001336576,0.1017106,0.002466757,0.00002527494,0.0000574528,0.00008966441,0.00001482655,0.002930762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08449824,"threshold_uncertainty_score":0.4537396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1004170172553601,"score_gpt":0.4303711173411418,"score_spread":0.3299541000857817,"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."}}