{"id":"W4411729192","doi":"10.1016/j.neuroimage.2025.121347","title":"Comparison of post-stroke white matter assessment using disconnectome-symptom mapping versus quantitative diffusion MRI","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Center for Medical Rehabilitation Research; National Institute of General Medical Sciences; National Institutes of Health; Deutsche Forschungsgemeinschaft; National Institute of Child Health and Human Development; Canadian Institutes of Health Research; U.S. Department of Veterans Affairs","keywords":"White matter; Diffusion MRI; Stroke (engine); Diffusion; Medicine; Psychology; Physical medicine and rehabilitation; Radiology; Magnetic resonance imaging; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002695818,0.0005086925,0.0004523288,0.001314177,0.0001671582,0.0007336753,0.0004017392,0.0005748108,0.0008245195],"category_scores_gemma":[0.005905084,0.000131814,0.0003957162,0.0006527245,0.0004053328,0.0006560917,0.0008069925,0.0002232897,0.0002701289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001582363,"about_ca_system_score_gemma":0.0001930699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008076717,"about_ca_topic_score_gemma":0.001884768,"domain_scores_codex":[0.9986097,0.000541925,0.0001730054,0.0004081371,0.0001899274,0.00007742183],"domain_scores_gemma":[0.997558,0.001005758,0.0006477504,0.0004460889,0.0002373532,0.0001050693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01258389,0.0003957928,0.8049123,0.0009759609,0.005274956,0.0004066378,0.001248238,0.005772369,0.06864687,0.0009520189,0.001163855,0.09766721],"study_design_scores_gemma":[0.0001032915,0.001143416,0.9785652,0.00003573478,0.0003119447,0.0008296214,0.0002744951,0.01059369,0.006391633,0.0006857326,0.001023242,0.0000419999],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922312,0.0003063503,0.005978588,0.00002621774,0.000007378147,0.00004362988,0.001021156,0.00004834756,0.0003371929],"genre_scores_gemma":[0.9930493,0.000114522,0.003918146,0.00001811751,0.00001219679,0.0001047568,0.002573998,0.00002191791,0.0001870073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002695818,"threshold_uncertainty_score":0.01425701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1056022796359809,"score_gpt":0.4432362714092338,"score_spread":0.3376339917732529,"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."}}