{"id":"W2499437061","doi":"10.1371/journal.pone.0159895","title":"Correction: Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study","year":2016,"lang":"en","type":"erratum","venue":"PLoS ONE","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Duchenne muscular dystrophy; Natural history; Muscular dystrophy; Bioinformatics; Medicine; Computational biology; Data science; Computer science; Biology; Internal medicine","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":[0.008225324,0.003427175,0.002801168,0.003916869,0.002918302,0.004014079,0.005036295,0.007873924,0.04232628],"category_scores_gemma":[0.1184132,0.001542645,0.002632455,0.002494617,0.00338946,0.002843306,0.002951152,0.01279975,0.01952119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003509999,"about_ca_system_score_gemma":0.007187691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01694405,"about_ca_topic_score_gemma":0.02360708,"domain_scores_codex":[0.9918965,0.001587493,0.001820349,0.001114904,0.003000777,0.000580061],"domain_scores_gemma":[0.9509619,0.01637265,0.002563673,0.00292246,0.02518,0.001999267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005205144,0.000005413895,0.0001319148,0.0002600711,0.00003781904,0.0004333579,0.0000423438,0.0000584008,0.0000669421,0.0008729501,0.9933422,0.004696457],"study_design_scores_gemma":[0.0001396856,0.00003628717,0.001686437,0.001148251,0.0001822259,0.002764376,0.0001586487,0.0005509924,0.0005983604,0.004652287,0.9879561,0.00012633],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001264863,0.001072388,0.0009849534,0.04992794,0.9453233,0.00001947734,0.001398425,0.0003242609,0.000822715],"genre_scores_gemma":[0.02127709,0.01415545,0.01510485,0.164376,0.6386881,0.0003825016,0.006208521,0.00292862,0.1368789],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04232628,"threshold_uncertainty_score":0.1415955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686448570068289,"score_gpt":0.2212667757800273,"score_spread":0.2044022900793444,"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."}}