{"id":"W2986730615","doi":"10.1093/geroni/igz038.2390","title":"AUGMENTATION INDEX IS A PREDICTOR OF CEREBRAL BLOOD FLOW ACROSS GLOBAL GRAY MATTER IN THE ELDERLY","year":2019,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Heart Institute; Institut Universitaire de Gériatrie de Montréal; Concordia University; Polytechnique Montréal; Montreal Clinical Research Institute; Université de Montréal","funders":"","keywords":"Arterial stiffness; Medicine; Cardiology; Cerebral blood flow; Internal medicine; Pulse wave velocity; Linear regression; Blood pressure; Cohort; Coefficient of variation; Mathematics; Statistics","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":[0.0004303538,0.0003488737,0.0002655488,0.0004495168,0.0001914165,0.0002957402,0.0001446884,0.0003381738,0.00151828],"category_scores_gemma":[0.001310988,0.0001218614,0.0003070878,0.0002760353,0.0001260817,0.0001742769,0.0002382122,0.0003531424,0.0002815328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009301848,"about_ca_system_score_gemma":0.0001509593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002144387,"about_ca_topic_score_gemma":0.002221402,"domain_scores_codex":[0.9999099,0.00002146146,0.00001112227,0.00002237953,0.00002176036,0.00001335866],"domain_scores_gemma":[0.9995365,0.0001411784,0.0001437626,0.00004226084,0.00007171649,0.00006446196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005133794,0.00007392553,0.9922207,0.00001979678,0.0001020104,0.00007768119,0.00005745095,0.0002178305,0.001813056,0.00002365167,0.0001957869,0.004684724],"study_design_scores_gemma":[0.000005146333,0.0001333508,0.9981678,0.000004249729,0.00003882921,0.0001274834,0.0000419982,0.001109157,0.0002088865,0.00006323934,0.00009662806,0.000003254281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986898,0.0002456503,0.0003565642,0.00003298839,0.000008116374,0.000006666034,0.0002372162,0.00001479682,0.0004081103],"genre_scores_gemma":[0.9992653,0.00005258771,0.000259552,0.000007922493,0.000008863485,0.000006549881,0.0001498972,0.000001714821,0.000247743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002144387,"threshold_uncertainty_score":0.00507915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01134055748853758,"score_gpt":0.3099817035156768,"score_spread":0.2986411460271392,"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."}}