{"id":"W2773225668","doi":"10.1016/j.mri.2017.12.002","title":"The potential role of IDEAL MRI for identification of lipids and hemorrhage in carotid artery plaques","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"U.S. Army Medical Research Acquisition Activity; Consortia for Improving Medicine with Innovation and Technology","keywords":"Medicine; Stenosis; Asymptomatic; Stroke (engine); Blood lipids; Internal medicine; Cardiology; Radiology; Nuclear medicine; Cholesterol","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007137556,0.0006003759,0.0004779249,0.001064008,0.000216755,0.0008705205,0.000538856,0.0005400327,0.0006030865],"category_scores_gemma":[0.01238409,0.0004221802,0.0001790534,0.0002790742,0.0008153252,0.001286913,0.0006296106,0.0004319233,0.0002475489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001640884,"about_ca_system_score_gemma":0.0003590254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003530638,"about_ca_topic_score_gemma":0.0006524623,"domain_scores_codex":[0.9983198,0.001048792,0.00007820984,0.0001625578,0.00032896,0.00006174234],"domain_scores_gemma":[0.9957771,0.002240304,0.0006549453,0.0004217167,0.0007188428,0.0001870566],"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":[0.005470445,0.0003828159,0.1657082,0.0007937404,0.0002622473,0.001155693,0.0006998224,0.0115079,0.474185,0.002726564,0.0005457433,0.3365619],"study_design_scores_gemma":[0.0002869923,0.007544469,0.3840501,0.0002133672,0.0005098082,0.01538953,0.001072632,0.2959284,0.2764065,0.01280482,0.0053655,0.0004278723],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8251968,0.003211124,0.1689667,0.0003936988,0.00005871096,0.0001052259,0.00007324403,0.00032701,0.001667469],"genre_scores_gemma":[0.847322,0.0009472601,0.1508926,0.0001143955,0.00007524458,0.00005230568,0.0000683327,0.00006850522,0.0004592923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007137556,"threshold_uncertainty_score":0.03774744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004580671652855212,"score_gpt":0.238003864714028,"score_spread":0.2334231930611727,"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."}}