{"id":"W2939958603","doi":"10.1002/acn3.779","title":"Neurofilament as a potential biomarker for spinal muscular atrophy","year":2019,"lang":"en","type":"article","venue":"Annals of Clinical and Translational Neurology","topic":"Neurogenetic and Muscular Disorders Research","field":"Medicine","cited_by":207,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Center for Advancing Translational Sciences; National Institutes of Health; National Institute for Health and Care Research; Cytokinetics; Strong; Ionis Pharmaceuticals; FibroGen; Ultragenyx Pharmaceutical; Children's Hospital of Philadelphia; Spinal Muscular Atrophy Foundation; FSHD Global Research Foundation; Pfizer; Sarepta Therapeutics; Muscular Dystrophy Association; U.S. Department of Defense; Sanofi; AveXis; Biogen","keywords":"SMA*; Medicine; Spinal muscular atrophy; Biomarker; Neuromuscular disease; Atrophy; Internal medicine; Neurofilament; Gastroenterology; Disease","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":[0.0008030075,0.0005702364,0.0004993489,0.0004417055,0.0001866309,0.0006497409,0.0003459187,0.0005010198,0.001333848],"category_scores_gemma":[0.001262454,0.0001753211,0.0002518686,0.0003905482,0.0001930215,0.0003300784,0.0002895705,0.0004733816,0.0002712335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003801791,"about_ca_system_score_gemma":0.0002098197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001008139,"about_ca_topic_score_gemma":0.002060509,"domain_scores_codex":[0.999605,0.00009855002,0.00003657726,0.0001078023,0.0001097869,0.00004231072],"domain_scores_gemma":[0.9990166,0.0001336764,0.0005745303,0.00002451845,0.0001627199,0.00008791001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004361723,0.0002064937,0.8884403,0.0005831469,0.0006425132,0.0003871541,0.0000961975,0.0003942288,0.05226561,0.00009159144,0.001416273,0.05111479],"study_design_scores_gemma":[0.00007006827,0.002651158,0.9778618,0.0001287208,0.0002608369,0.00154199,0.0001067475,0.001211609,0.01368139,0.00008928718,0.002376609,0.00001965746],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832439,0.01331282,0.0007552618,0.0002034577,0.00004181436,0.00003717178,0.001059307,0.00008220787,0.001264107],"genre_scores_gemma":[0.9953083,0.001617231,0.001414269,0.0001484176,0.00003633871,0.00003844632,0.0005810893,0.000005760234,0.0008501359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001333848,"threshold_uncertainty_score":0.004462123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1347300512912833,"score_gpt":0.4597407997651151,"score_spread":0.3250107484738318,"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."}}