{"id":"W3037795616","doi":"10.1093/brain/awaa162","title":"Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability","year":2020,"lang":"en","type":"article","venue":"Brain","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Montreal Neurological Institute and Hospital; Université de Montréal; Université du Québec à Montréal; Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; Institut de Valorisation des Données; Fondation pour l'Aide à la Recherche sur la Sclérose en Plaques; National Institutes of Health; Vetenskapsrådet; Hjärnfonden","keywords":"Corticospinal tract; Spinal cord; Lesion; Medicine; Expanded Disability Status Scale; Pyramidal tracts; Multiple sclerosis; White matter; Central nervous system disease; Magnetic resonance imaging; Pathology; Anatomy; Diffusion MRI; 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":[0.0003144101,0.0002069783,0.0002444616,0.001488752,0.0002374774,0.0003657539,0.0001803046,0.0002625801,0.001589248],"category_scores_gemma":[0.001956721,0.0001304394,0.0001647639,0.0006820988,0.000343659,0.0002513346,0.0004025474,0.0001599179,0.0002493062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001679954,"about_ca_system_score_gemma":0.0001776818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003231616,"about_ca_topic_score_gemma":0.005604302,"domain_scores_codex":[0.9997565,0.00004205165,0.00003730661,0.00007587698,0.00005895267,0.00002925806],"domain_scores_gemma":[0.9988476,0.0003367065,0.0004556147,0.00009823138,0.0001455577,0.0001164039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001556921,0.000009646105,0.9904196,0.00001677868,0.00005965391,0.0002451368,0.00009654799,0.0001843692,0.004421616,0.00001486007,0.00004719548,0.004328853],"study_design_scores_gemma":[0.000002329637,0.0000275185,0.9982994,0.00000292997,0.00001161611,0.001095153,0.00005904346,0.0002046175,0.0002102363,0.00002617515,0.0000578204,0.000003118809],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993358,0.0001758603,0.0001197779,0.00001166742,6.55224e-7,0.000002758088,0.00008318526,0.000006576628,0.0002635838],"genre_scores_gemma":[0.9997315,0.0000437534,0.00007776453,0.000002513185,0.00000175621,0.00000239259,0.00008566214,0.000001622144,0.00005298445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003231616,"threshold_uncertainty_score":0.006425619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07502208406369552,"score_gpt":0.302675742191108,"score_spread":0.2276536581274125,"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."}}