{"id":"W4415709898","doi":"10.1177/15910199251389654","title":"MRI quantitative biomarkers focusing on apparent diffusion coefficient for predicting hemorrhagic transformation after thrombectomy: A PRISMA-DTA systematic review and meta-analysis","year":2025,"lang":"en","type":"article","venue":"Interventional Neuroradiology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"","keywords":"Magnetic resonance imaging; Meta-analysis; Diffusion MRI; Effective diffusion coefficient; Stroke (engine); Imaging biomarker; Magnetic resonance elastography; Publication bias; Bivariate analysis","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":[0.02789479,0.003499386,0.02246292,0.009485951,0.0009227484,0.004341009,0.003056769,0.002638708,0.005489464],"category_scores_gemma":[0.06623863,0.001672929,0.04391974,0.009451103,0.001073395,0.002427919,0.002562719,0.002125856,0.0005239455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003486127,"about_ca_system_score_gemma":0.007280446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007726148,"about_ca_topic_score_gemma":0.01623873,"domain_scores_codex":[0.9805194,0.008751278,0.006137366,0.001764488,0.002337259,0.0004901829],"domain_scores_gemma":[0.9659543,0.02421287,0.005750559,0.001154979,0.00267013,0.000257259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0007169201,0.00001701929,0.002382404,0.6400315,0.3469388,0.00007520743,0.00008251574,0.0005031753,0.0001503479,0.0001950752,0.0006751388,0.008231792],"study_design_scores_gemma":[0.0004937353,0.0001014892,0.002485925,0.05745465,0.9363829,0.00007353679,0.00003481256,0.000332721,0.00009056806,0.0003299739,0.002188766,0.00003095927],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0033261,0.9893161,0.002621398,0.0004075827,0.0002039511,0.001773507,0.001912607,0.00007838353,0.0003603078],"genre_scores_gemma":[0.1536891,0.8146399,0.01234547,0.001910727,0.0004088088,0.01290679,0.003280039,0.0001104125,0.0007087652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02789479,"threshold_uncertainty_score":0.1475235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03881718547322182,"score_gpt":0.3389979264571124,"score_spread":0.3001807409838906,"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."}}