{"id":"W4292553565","doi":"10.3389/fnagi.2022.941864","title":"An exploratory causal analysis of the relationships between the brain age gap and cardiovascular risk factors","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Open Neuroscience Platform; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Causal inference; Confounding; Context (archaeology); Spurious relationship; Univariate; Causal structure; Psychology; Medicine; Multivariate statistics; Computer science; Internal medicine; Machine learning; Biology; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.01336053,0.000855937,0.0007639338,0.002214927,0.0007023779,0.00106455,0.0009825302,0.0008226897,0.007381056],"category_scores_gemma":[0.04054149,0.0004142596,0.003023241,0.001536501,0.001059343,0.001320023,0.00197944,0.001333533,0.000238716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009306513,"about_ca_system_score_gemma":0.002326818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008307195,"about_ca_topic_score_gemma":0.00541543,"domain_scores_codex":[0.9947394,0.003912523,0.0001274889,0.0007482247,0.0002488762,0.0002235266],"domain_scores_gemma":[0.9552213,0.0400403,0.001976166,0.001534848,0.0008666227,0.0003607591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002453167,0.0007552211,0.3448196,0.001533197,0.0066406,0.003045462,0.003330435,0.1593011,0.004267091,0.2822407,0.006471302,0.1851422],"study_design_scores_gemma":[0.0002222192,0.0007111358,0.08907269,0.0002706797,0.002468052,0.0008556774,0.0009081239,0.5903482,0.001774307,0.3063995,0.006833336,0.0001360142],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2390431,0.0009936613,0.7517999,0.00184025,0.00009042053,0.0004424659,0.002786521,0.0004821238,0.002521618],"genre_scores_gemma":[0.9115823,0.0004096664,0.08532146,0.0001926557,0.00005522395,0.0005237709,0.0008236734,0.00003858512,0.00105268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01336053,"threshold_uncertainty_score":0.07065809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04028175569786172,"score_gpt":0.2522932743264977,"score_spread":0.212011518628636,"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."}}