{"id":"W2981116199","doi":"10.1016/j.jalz.2019.06.3430","title":"P3‐397: CHARACTERIZATION OF LENTICULOSTRIATE ARTERIES USING ARTERIAL SPIN LABELING AND HIGH‐RESOLUTION 3D BLACK‐BLOOD MRI AS AN IMAGING MARKER IN VASCULAR COGNITIVE IMPAIRMENT AND DEMENTIA","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Magnetic resonance imaging; Montreal Cognitive Assessment; Cerebral blood flow; Cardiology; Vascular dementia; Middle cerebral artery; Internal medicine; Dementia; Nuclear medicine; Radiology; Ischemia","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004908113,0.0002599011,0.0001600549,0.0008470814,0.0001918459,0.00048897,0.0002000995,0.0002704743,0.001721176],"category_scores_gemma":[0.0005602401,0.0001504256,0.0001964385,0.0003433087,0.0002266441,0.0002272914,0.0002041085,0.0001801267,0.0002071449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001420538,"about_ca_system_score_gemma":0.0002107122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003084918,"about_ca_topic_score_gemma":0.002363066,"domain_scores_codex":[0.9999274,0.00002116503,0.000004304411,0.00001791178,0.00001600857,0.0000132172],"domain_scores_gemma":[0.9998436,0.00003889236,0.00004381568,0.00002263432,0.00002401856,0.00002697113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003670484,0.0004395183,0.579779,0.000234916,0.0003412143,0.003358783,0.0009238548,0.001350737,0.3396447,0.0004836528,0.0004698812,0.06930325],"study_design_scores_gemma":[0.00004872613,0.0005578469,0.9735851,0.00002101828,0.00008648745,0.003074085,0.0002731445,0.00572614,0.01530353,0.0005200122,0.0007851261,0.00001886855],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980044,0.0001710855,0.00116712,0.00001508121,0.000001633553,0.00001515584,0.0001132428,0.00001751698,0.000494769],"genre_scores_gemma":[0.9972692,0.0001377119,0.001983894,0.00001586319,0.000007295282,0.00003531462,0.0001194536,0.000009659628,0.0004216944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003084918,"threshold_uncertainty_score":0.006133914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008729672142767576,"score_gpt":0.2403546483425216,"score_spread":0.2316249761997541,"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."}}