{"id":"W4414867530","doi":"10.1016/j.mri.2025.110539","title":"Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; Vanderbilt Kennedy Center, Vanderbilt University Medical Center; Vanderbilt Institute for Clinical and Translational Research; National Institute on Aging; National Cancer Institute; National Institutes of Health; Vanderbilt University","keywords":"Anisotropy; Voxel; Diffusion MRI; Sensitivity (control systems); Fractional anisotropy; Tractography; Thermal diffusivity","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":[0.02567525,0.0007616847,0.00073399,0.001699263,0.0005298296,0.001614275,0.0006070498,0.0006652048,0.0008660471],"category_scores_gemma":[0.1333985,0.0005469791,0.0007285758,0.001216917,0.002039282,0.001116974,0.001416252,0.0007100262,0.0002352282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007441431,"about_ca_system_score_gemma":0.0005308955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002715417,"about_ca_topic_score_gemma":0.001779844,"domain_scores_codex":[0.9873127,0.006102149,0.001017388,0.003030386,0.002298945,0.000238369],"domain_scores_gemma":[0.8484231,0.1204443,0.01455907,0.01153309,0.004519049,0.0005212855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002997839,0.0001307401,0.5953021,0.0018206,0.005018346,0.0009143864,0.003013189,0.1019875,0.08929744,0.007935271,0.001828228,0.1897544],"study_design_scores_gemma":[0.0001083341,0.0005888273,0.778712,0.0002636146,0.0009381979,0.003960909,0.0004161215,0.1461934,0.03453353,0.03070197,0.003379276,0.0002037801],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7264407,0.004862406,0.2636183,0.0004985872,0.0001455766,0.0002168122,0.0008774178,0.0006175195,0.002722786],"genre_scores_gemma":[0.9834457,0.0003212203,0.01537039,0.00008014104,0.00004075458,0.00006333484,0.0003919572,0.0001274359,0.0001590148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02567525,"threshold_uncertainty_score":0.1357853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02186958569687273,"score_gpt":0.3342527161948148,"score_spread":0.3123831304979421,"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."}}