{"id":"W4200205313","doi":"10.1002/nbm.4685","title":"Validation of cardiac diffusion tensor imaging sequences: A multicentre test–retest phantom study","year":2021,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Office of AIDS Research; NIHR Oxford Biomedical Research Centre; National Heart, Lung, and Blood Institute; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute of Biomedical Imaging and Bioengineering; British Heart Foundation; National Institute for Health and Care Research","keywords":"Reproducibility; Repeatability; Diffusion MRI; Imaging phantom; Fractional anisotropy; Materials science; Biomedical engineering; Nuclear medicine; Nuclear magnetic resonance; Artifact (error); Analytical Chemistry (journal); Medicine; Chemistry; Magnetic resonance imaging; Computer science; Radiology; Physics; Artificial intelligence; Chromatography","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":[0.02715069,0.001457817,0.001044738,0.0008152071,0.0008200833,0.00108807,0.001326323,0.001530202,0.0006218285],"category_scores_gemma":[0.04724441,0.00105998,0.001098685,0.0008835084,0.001824415,0.0008964779,0.001177371,0.001036741,0.0006471046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000892156,"about_ca_system_score_gemma":0.0007267814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002378791,"about_ca_topic_score_gemma":0.003698058,"domain_scores_codex":[0.9776669,0.01192553,0.001470747,0.004967403,0.003441297,0.0005282022],"domain_scores_gemma":[0.944018,0.02325681,0.006876993,0.01341356,0.01145124,0.0009835652],"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":[0.01421259,0.005494485,0.1596015,0.0007194901,0.003462646,0.0005474197,0.01243233,0.01145645,0.7197664,0.0007215384,0.001623467,0.06996172],"study_design_scores_gemma":[0.001374146,0.06449839,0.6541159,0.000131929,0.0030003,0.002861339,0.001488729,0.02901647,0.2278671,0.000797049,0.01429527,0.0005533744],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9586209,0.0007869161,0.037999,0.0001015225,0.0001398212,0.0005341227,0.0003599904,0.0003268521,0.001130751],"genre_scores_gemma":[0.9631021,0.0002203654,0.03287025,0.0002140622,0.00006526314,0.0006715041,0.001011765,0.0003370478,0.001507707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02715069,"threshold_uncertainty_score":0.1435883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04574986128022169,"score_gpt":0.3680587431632073,"score_spread":0.3223088818829856,"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."}}