{"id":"W2794584704","doi":"10.1002/jmri.26028","title":"Variable impact of CSF flow suppression on quantitative 3.0T intracranial vessel wall measurements","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Philips (Canada); CARE Canada","funders":"National Institutes of Health; Centre National de la Recherche Scientifique; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; American Heart Association","keywords":"Flip angle; Lumen (anatomy); Cerebrospinal fluid; Nuclear medicine; Basilar artery; Magnetic resonance imaging; Medicine; Biomedical engineering; Materials science; Radiology; Internal medicine","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":[0.0004229321,0.0001429421,0.0003545427,0.0001398104,0.00006947332,0.00001603498,0.0001570768,0.00003992094,0.0002540275],"category_scores_gemma":[0.0002795258,0.0001035825,0.0001329778,0.0002275112,0.0001365139,0.0001815008,0.00002661457,0.0002614699,0.000007123263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001201839,"about_ca_system_score_gemma":0.0001692321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002599241,"about_ca_topic_score_gemma":5.265062e-7,"domain_scores_codex":[0.9986115,0.0000412266,0.0005245445,0.0001522937,0.0004494858,0.000220971],"domain_scores_gemma":[0.998336,0.00008182044,0.0004099708,0.0002434156,0.0008127838,0.0001159791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003352397,0.001038273,0.01681261,0.00007540851,0.00003772275,0.00007891797,0.0007717931,0.0004617346,0.5851848,0.0009813227,0.02374878,0.3674563],"study_design_scores_gemma":[0.01823035,0.0298336,0.5070227,0.01153767,0.0007903095,0.002216673,0.0005889628,0.1135746,0.1669907,0.02798185,0.1200281,0.001204501],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6581161,0.01230037,0.3107934,0.004109092,0.0005643643,0.001234664,0.00005354713,0.00008751816,0.01274097],"genre_scores_gemma":[0.6163657,0.0002262467,0.3827944,0.0002017431,0.0002489189,0.000006115451,0.000001925176,0.0000252118,0.0001297858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4902101,"threshold_uncertainty_score":0.4223971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03100795427251091,"score_gpt":0.3587427259514334,"score_spread":0.3277347716789225,"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."}}