{"id":"W3177207463","doi":"10.1002/mrm.28886","title":"Design and characterization of a 3D‐printed axon‐mimetic phantom for diffusion MRI","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fondation Brain Canada","keywords":"Kurtosis; Imaging phantom; Materials science; Biomedical engineering; Diffusion MRI; Reproducibility; Thermal diffusivity; Diffusion; Effective diffusion coefficient; Nuclear magnetic resonance; Nuclear medicine; Chemistry; Magnetic resonance imaging; Physics; Mathematics; Medicine; Radiology","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":[0.00120653,0.0008398364,0.0004175157,0.0005640728,0.0002788579,0.0006289419,0.0006979041,0.0008184446,0.0009741551],"category_scores_gemma":[0.001746809,0.0004989155,0.0003392858,0.0002736124,0.0004926344,0.0005719169,0.0003327441,0.000490885,0.0006640498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006073487,"about_ca_system_score_gemma":0.0005995558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004045464,"about_ca_topic_score_gemma":0.0004893556,"domain_scores_codex":[0.9995603,0.00007694704,0.00002856706,0.0000975242,0.0002046098,0.00003199872],"domain_scores_gemma":[0.9989259,0.0004468113,0.000253501,0.0001184068,0.0001609688,0.00009439148],"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":[0.0000484107,0.00003458952,0.0001702796,0.00009440133,0.000005485978,0.0001091996,0.000038668,0.001567696,0.9927362,0.0003671579,0.0001509644,0.004677066],"study_design_scores_gemma":[0.0000182707,0.0002716182,0.0009137125,0.00001283783,0.00001718696,0.0004591246,0.00001487144,0.01205552,0.9801121,0.0001769303,0.005920007,0.00002780996],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3522814,0.002119193,0.6354176,0.0006115983,0.0001623518,0.001172252,0.0009425562,0.002479393,0.004813581],"genre_scores_gemma":[0.4313925,0.001347879,0.5599634,0.0003064449,0.00004896889,0.001542123,0.0008320699,0.0002840728,0.004282551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00120653,"threshold_uncertainty_score":0.006380856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05119818267325604,"score_gpt":0.3368287378173702,"score_spread":0.2856305551441141,"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."}}