{"id":"W2375577403","doi":"10.1038/ncomms11479","title":"The somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes","year":2016,"lang":"en","type":"erratum","venue":"Nature Communications","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1800,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute in Oncology and Hematology; BC Cancer Agency; Kingston General Hospital; Queen's University","funders":"Cancer Research UK Cambridge Institute, University of Cambridge; NIHR Cambridge Biomedical Research Centre; BC Cancer Agency; National Institute for Health and Care Research; University of Cambridge; Cancer Research UK","keywords":"Breast cancer; Biology; Mutation; Transcriptome; Gene; Genetic heterogeneity; Allele; Genetics; Somatic cell; Tumour heterogeneity; Cancer research; Cancer; Computational biology; Phenotype; Gene expression","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":[0.0002020861,0.0001692761,0.0002341434,0.000412916,0.0001805719,0.0004388075,0.00009285717,0.0003031678,0.001451667],"category_scores_gemma":[0.0006425768,0.0001111055,0.0001972277,0.0007942655,0.000198469,0.0001093687,0.0001514538,0.0002173019,0.0003882869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003001622,"about_ca_system_score_gemma":0.0001637995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00244571,"about_ca_topic_score_gemma":0.007251558,"domain_scores_codex":[0.9998635,0.00001566352,0.00001266091,0.00003712072,0.00004481126,0.00002620509],"domain_scores_gemma":[0.9997868,0.00009429722,0.00004345371,0.00002518433,0.0000350681,0.00001516201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000744702,0.00003480751,0.5178072,0.000252134,0.00009703264,0.002207819,0.0009251942,0.001577756,0.3933044,0.0006008549,0.002493577,0.07995456],"study_design_scores_gemma":[0.00000985409,0.00006649338,0.9609079,0.00001637061,0.00006713728,0.004924206,0.0003237332,0.001530991,0.02044797,0.0004177736,0.01126923,0.00001840614],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940029,0.001125439,0.001410531,0.0002000597,0.00002650147,0.000007306826,0.001980827,0.00004353921,0.001202947],"genre_scores_gemma":[0.9900792,0.00133595,0.003769384,0.0001441584,0.00001652406,0.00001291353,0.002299577,0.00003092478,0.002311442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00244571,"threshold_uncertainty_score":0.004862905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006894050141487316,"score_gpt":0.2478468984998881,"score_spread":0.2409528483584008,"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."}}