{"id":"W2798240981","doi":"10.1016/j.mri.2018.04.001","title":"Effect of cardiac-related translational motion in diffusion MRI of the spinal cord","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Canada Foundation for Innovation","keywords":"Diffusion MRI; Spinal cord; Imaging phantom; SIGNAL (programming language); Cord; Diffusion; Medicine; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Nuclear medicine; Computer science; Radiology; Surgery","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":[0.0007415766,0.0003841379,0.0002517867,0.0003318407,0.0003341629,0.0006070331,0.0002566105,0.0005944938,0.002868304],"category_scores_gemma":[0.00587258,0.000232384,0.0002459504,0.0002975431,0.0004442491,0.000491299,0.0003293008,0.0005217601,0.0002644377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002735289,"about_ca_system_score_gemma":0.0004217395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002514832,"about_ca_topic_score_gemma":0.00248331,"domain_scores_codex":[0.9998348,0.00007239259,0.00001266742,0.00002220684,0.00002616645,0.00003178933],"domain_scores_gemma":[0.9985248,0.001079482,0.000120344,0.00008153032,0.00008988765,0.0001039805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.006094488,0.000287082,0.004490484,0.0004454566,0.0002214616,0.001440204,0.000461926,0.009311907,0.9475659,0.0007856662,0.0004909752,0.02840449],"study_design_scores_gemma":[0.0005399015,0.005959107,0.2554405,0.0001782705,0.001600136,0.003741881,0.0004658261,0.07061973,0.6553337,0.00151239,0.004467299,0.0001411985],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837809,0.003595793,0.009878661,0.0002775168,0.0001149117,0.00005306896,0.0001791371,0.0001545262,0.001965588],"genre_scores_gemma":[0.9961093,0.000988848,0.001650687,0.000100464,0.00006811153,0.00001429197,0.0001309637,0.0001116673,0.0008255921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002868304,"threshold_uncertainty_score":0.009595394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01470428252915885,"score_gpt":0.3213850486417121,"score_spread":0.3066807661125532,"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."}}