{"id":"W4390198800","doi":"10.1002/alz.079809","title":"Genetic Architecture of Cortical Thickness and White Matter hyperintensities: Evidence of Gene‐Environment Interaction with Cardiovascular Health and Late‐Life Depression","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Dementia Research Alliance; Sunnybrook Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Biobank; Genome-wide association study; Genetic architecture; Context (archaeology); Locus (genetics); Genetic association; Depression (economics); Hyperintensity; Disease; Neuroscience; Genetics; Single-nucleotide polymorphism; Biology; Medicine; Gene; Internal medicine; Quantitative trait locus; Magnetic resonance imaging; Genotype","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007984442,0.0004728393,0.0003182094,0.001060732,0.0004757371,0.0008132329,0.0005750999,0.0005250709,0.002604662],"category_scores_gemma":[0.002401466,0.0002773894,0.00067607,0.001277323,0.0007809484,0.000166158,0.0005689519,0.0005856543,0.000152532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004339615,"about_ca_system_score_gemma":0.0004993375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03769121,"about_ca_topic_score_gemma":0.03739446,"domain_scores_codex":[0.9991471,0.0002374899,0.00007225068,0.0003338099,0.0001052621,0.0001040316],"domain_scores_gemma":[0.9978434,0.0007399273,0.0007433846,0.000224376,0.0002057469,0.0002432102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008659807,0.00004710207,0.9826798,0.0000639842,0.001365194,0.0006101807,0.0002910304,0.0003558575,0.009228182,0.0002676864,0.0003361868,0.00388882],"study_design_scores_gemma":[0.000009578823,0.00003207655,0.9989269,0.000009230112,0.0001294778,0.0001824004,0.00005554056,0.0002336308,0.0002220788,0.0001174924,0.00007678651,0.000004688834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977696,0.0005855496,0.0004410801,0.0001126406,0.000008241636,0.000006513258,0.0006266293,0.00001365501,0.0004361354],"genre_scores_gemma":[0.9991195,0.000138419,0.0003207932,0.00003257429,0.000006858237,0.00000559668,0.0001944572,0.000006376675,0.0001754098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03769121,"threshold_uncertainty_score":0.07494366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964654918676922,"score_gpt":0.2550658902983837,"score_spread":0.2354193411116145,"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."}}