{"id":"W2233252933","doi":"10.1038/npjgenmed.2015.12","title":"Whole-genome sequencing expands diagnostic utility and improves clinical management in paediatric medicine","year":2016,"lang":"en","type":"article","venue":"npj Genomic Medicine","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":377,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Institute for Clinical Evaluative Sciences; University of Toronto; SickKids Foundation; Hospital for Sick Children; Public Health Ontario","funders":"Canadian Institutes of Health Research; Hospital for Sick Children; University of Toronto; Genome Canada; GlaxoSmithKline","keywords":"Indel; Whole genome sequencing; Copy-number variation; Genetic testing; Genetics; Medical genetics; DNA sequencing; Missense mutation; Human genetics; Biology; Medicine; Mutation; Gene; Bioinformatics; Genome; Computational biology; Single-nucleotide polymorphism; Genotype","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":[0.006245996,0.0006943832,0.0008306235,0.001952775,0.0002411344,0.00142132,0.0006357669,0.001148187,0.005554598],"category_scores_gemma":[0.01887814,0.0003760321,0.0004771579,0.001419617,0.0007538652,0.001557315,0.001231127,0.0009315569,0.001765634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004601793,"about_ca_system_score_gemma":0.0007251612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008106843,"about_ca_topic_score_gemma":0.0009027352,"domain_scores_codex":[0.9963273,0.002227745,0.0002315231,0.0005085312,0.0005849687,0.0001199386],"domain_scores_gemma":[0.9896445,0.006611921,0.001077323,0.0008949192,0.001363278,0.0004079957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006495762,0.0001989185,0.3023497,0.0009713222,0.0001829204,0.001981623,0.0004423264,0.002083045,0.01552111,0.002892671,0.01483085,0.6578959],"study_design_scores_gemma":[0.0001552986,0.0009467506,0.8292538,0.001415741,0.0004080916,0.02569981,0.0007292472,0.01484783,0.01339598,0.01534334,0.09767088,0.0001332143],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6361877,0.09693033,0.1850854,0.02521092,0.001185415,0.0005198955,0.007865512,0.004339393,0.04267539],"genre_scores_gemma":[0.8457091,0.03209803,0.1105951,0.003820538,0.001332312,0.0001941505,0.003276862,0.0004625407,0.002511309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006245996,"threshold_uncertainty_score":0.03303242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02208723545716237,"score_gpt":0.2907988927803203,"score_spread":0.2687116573231579,"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."}}