{"id":"W3183200901","doi":"10.1111/ene.15027","title":"Diffusion magnetic resonance imaging reveals tract‐specific microstructural correlates of electrophysiological impairments in non‐myelopathic and myelopathic spinal cord compression","year":2021,"lang":"en","type":"article","venue":"European Journal of Neurology","topic":"Cervical and Thoracic Myelopathy","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Ministerstvo Zdravotnictví Ceské Republiky; Masarykova Univerzita; Canadian Institutes of Health Research; Agentura Pro Zdravotnický Výzkum České Republiky; Central European Institute of Technology; Ministerstvo Školství, Mládeže a Tělovýchovy","keywords":"Diffusion MRI; Magnetic resonance imaging; Medicine; Spinal cord; Spinal cord compression; Corticospinal tract; Myelopathy; Diffusion-Weighted Magnetic Resonance Imaging; Neuroscience; Radiology; Psychology","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":[0.0002973608,0.0002681751,0.0001499616,0.0008027354,0.0001568682,0.0002312894,0.0001473036,0.0003624366,0.001585364],"category_scores_gemma":[0.001154903,0.000104425,0.0001184518,0.0002450006,0.0003991832,0.0002864889,0.0002326933,0.0001641582,0.0001340432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002426822,"about_ca_system_score_gemma":0.0001657305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001940032,"about_ca_topic_score_gemma":0.003289305,"domain_scores_codex":[0.9999224,0.00001094011,0.00001321564,0.00002367497,0.00001295317,0.00001681342],"domain_scores_gemma":[0.9995531,0.00009281721,0.0002075219,0.00003053649,0.00005578486,0.00006017481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001919725,0.000143032,0.8177598,0.0002455386,0.0002129955,0.003113753,0.0004365009,0.0005514571,0.1530975,0.0001682676,0.0002122305,0.02213921],"study_design_scores_gemma":[0.00001651498,0.0001851967,0.9920867,0.000009892837,0.00003179635,0.004133704,0.00008437863,0.0003415748,0.002961671,0.00006021516,0.00008382569,0.000004506066],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993227,0.0002519888,0.0001821408,0.00001458338,9.024122e-7,0.00000567825,0.00004571629,0.000004009522,0.0001722433],"genre_scores_gemma":[0.9996694,0.00006916171,0.0001437906,0.000006388636,0.000001990056,0.000002788525,0.00005912742,9.848551e-7,0.00004621707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001940032,"threshold_uncertainty_score":0.005303562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184859749158485,"score_gpt":0.2556280536195052,"score_spread":0.2437794561279204,"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."}}