{"id":"W2142154934","doi":"10.1002/mrm.25107","title":"Biomimetic phantom for the validation of diffusion magnetic resonance imaging","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; University of Manchester; Cancer Research UK; European Commission; Ministère des relations internationales et de la Francophonie","keywords":"Imaging phantom; Diffusion MRI; Materials science; Fractional anisotropy; Scanner; White matter; Magnetic resonance imaging; Biomedical engineering; Nuclear magnetic resonance; Reproducibility; Diffusion; Nuclear medicine; Medicine; Optics; Physics; Chemistry; Radiology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003093517,0.000965771,0.000365901,0.0007654809,0.000355683,0.0004500712,0.0006540901,0.001074062,0.002328691],"category_scores_gemma":[0.003617682,0.0003201237,0.0003456021,0.0003988264,0.0006616987,0.0006915808,0.0004876579,0.0006149418,0.0009051916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003771767,"about_ca_system_score_gemma":0.00053438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002486742,"about_ca_topic_score_gemma":0.0004253083,"domain_scores_codex":[0.998965,0.0002550214,0.0001030697,0.0001994761,0.0004373681,0.00004000421],"domain_scores_gemma":[0.9975582,0.0009331358,0.0005059977,0.0004305796,0.0004655703,0.0001064895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005743738,0.00007146991,0.0002461653,0.0001368196,0.000009857436,0.00004090246,0.00001852293,0.0004169628,0.9945866,0.000450259,0.0001463415,0.00381868],"study_design_scores_gemma":[0.00002783615,0.0007570171,0.002181631,0.00005423901,0.00005176826,0.001100859,0.00002405871,0.005128704,0.9787887,0.0003251834,0.01153702,0.0000229542],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2692473,0.007141867,0.7110074,0.0006918552,0.0006832413,0.001398267,0.001399817,0.002473996,0.00595624],"genre_scores_gemma":[0.352132,0.003050576,0.6371532,0.0003057157,0.00008604754,0.001703453,0.001901764,0.0002289138,0.003438372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003093517,"threshold_uncertainty_score":0.01636022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03869616698733432,"score_gpt":0.343438517391339,"score_spread":0.3047423504040047,"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."}}