{"id":"W4411010217","doi":"10.1016/j.mri.2025.110445","title":"Comparing single-shot EPI and 2D-navigated, multi-shot EPI diffusion tensor imaging acquisitions in the lumbar spinal cord at 3T","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt University; Society for Anthropological Sciences; National Institutes of Health; National Multiple Sclerosis Society","keywords":"Single shot; Shot (pellet); Diffusion MRI; Spinal cord; Lumbar; Medicine; Anatomy; Materials science; Radiology; Physics; Magnetic resonance imaging; Optics","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":[0.001480004,0.0003955991,0.0003803404,0.0005854755,0.0002815677,0.0006951381,0.0003653319,0.0006423965,0.0006586739],"category_scores_gemma":[0.003504166,0.0002929975,0.0002835831,0.000312954,0.0003417859,0.0006304534,0.000398169,0.0003237092,0.0001518348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001988935,"about_ca_system_score_gemma":0.0003692649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001418731,"about_ca_topic_score_gemma":0.004168918,"domain_scores_codex":[0.9996966,0.00007782875,0.0000315267,0.00009917276,0.00006882755,0.00002592737],"domain_scores_gemma":[0.9991339,0.0002233773,0.0001670127,0.0001242181,0.0002840705,0.00006743785],"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":[0.003545636,0.0004243843,0.06423758,0.0008583213,0.001059702,0.001288255,0.001141528,0.005331522,0.8374311,0.000885808,0.00114522,0.08265094],"study_design_scores_gemma":[0.000346492,0.005212922,0.6581433,0.0001175689,0.001654636,0.01230037,0.0008554105,0.03459936,0.2790613,0.002869911,0.004654667,0.0001840375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673483,0.0009272476,0.03028421,0.0001080348,0.00002569208,0.00008463205,0.0003282781,0.0001606563,0.0007328671],"genre_scores_gemma":[0.9565614,0.0007780545,0.04095067,0.000129014,0.0000536705,0.0001466607,0.0006337953,0.0001076465,0.0006390325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001480004,"threshold_uncertainty_score":0.007827044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08584864028324021,"score_gpt":0.367455365530476,"score_spread":0.2816067252472358,"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."}}