{"id":"W4363674118","doi":"10.1016/j.biopsych.2023.02.201","title":"18. 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":"Biological Psychiatry","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Hyperintensity; Context (archaeology); Depression (economics); Genetic architecture; Disease; Cognition; Neuroscience; Relevance (law); Intervention (counseling); White matter; Psychology; Medicine; Gerontology; Gene; Psychiatry; Biology; Genetics; Magnetic resonance imaging; Internal medicine; Quantitative trait locus","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":[0.0004904257,0.0001786385,0.0003558991,0.0000431118,0.0001048176,0.000007704587,0.00009992663,0.0001087752,0.0002749307],"category_scores_gemma":[0.00005241527,0.0001221962,0.00006670835,0.0001175921,0.0005631265,0.00006646108,0.0002077508,0.0002526133,0.00004144726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000438072,"about_ca_system_score_gemma":0.00001942541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009589727,"about_ca_topic_score_gemma":0.000007662448,"domain_scores_codex":[0.9981387,0.0003301961,0.000348341,0.0005960661,0.000295567,0.0002911786],"domain_scores_gemma":[0.9991604,0.0001304591,0.0001475235,0.0003258176,0.000004655789,0.0002311295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001741973,0.00004434547,0.9892551,0.0001244212,0.00003786107,0.000003448454,0.0003905469,0.002695489,0.002907187,0.00000115574,0.00006251116,0.004303738],"study_design_scores_gemma":[0.0002792992,0.0004168665,0.997516,0.0001944461,0.00002309645,0.00004683331,0.0006877779,0.0003229011,0.00008426636,0.00009185213,0.0001938811,0.0001428146],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926071,0.001607195,0.004270842,0.0009252211,0.00007686317,0.0003778809,0.000007989674,0.00002244032,0.0001044829],"genre_scores_gemma":[0.9923902,0.001767254,0.004747164,0.001011633,0.00002841589,0.00002197289,0.000005061742,0.00001416265,0.00001420232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008260867,"threshold_uncertainty_score":0.4983017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03404441600127887,"score_gpt":0.267380621845752,"score_spread":0.2333362058444731,"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."}}