{"id":"W3191375198","doi":"10.1038/s41467-021-25172-8","title":"Interacting evolutionary pressures drive mutation dynamics and health outcomes in aging blood","year":2021,"lang":"en","type":"article","venue":"Nature Communications","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; Princess Margaret Cancer Centre; Wilfrid Laurier University; Vector Institute; University of Toronto; Ontario Institute for Cancer Research","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; National Cancer Institute; Government of Canada; Government of Ontario; Canadian Institutes of Health Research; Ontario Genomics; Genome Canada; Vector Institute; Canadian Institute for Advanced Research; Memorial Sloan-Kettering Cancer Center","keywords":"Somatic evolution in cancer; Biology; Haematopoiesis; Disease; Evolutionary dynamics; Genetics; Somatic cell; Mutation; Population; Negative selection; Myeloid leukemia; Stem cell; Evolutionary biology; Genome; Gene; Immunology; Medicine; Internal medicine","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":[0.0007116534,0.0003390748,0.0003927634,0.0004360302,0.0003168372,0.0007312556,0.0005705566,0.0008328917,0.001499317],"category_scores_gemma":[0.002695546,0.0002412172,0.0005340131,0.0002566188,0.0008141557,0.000653757,0.0006017126,0.0006720145,0.0001685044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006823702,"about_ca_system_score_gemma":0.0004565058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01034915,"about_ca_topic_score_gemma":0.008924975,"domain_scores_codex":[0.9998519,0.00005297426,0.000004744809,0.00004644243,0.00001097366,0.00003284112],"domain_scores_gemma":[0.9995198,0.0002257045,0.00009757142,0.00002781913,0.0000393922,0.00008960696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002446593,0.0001240986,0.1653382,0.00006318886,0.0002058881,0.0005462176,0.0004013444,0.7936733,0.005444429,0.01563897,0.001339388,0.01698036],"study_design_scores_gemma":[0.00002053246,0.00006512922,0.0195198,0.00001258445,0.00004175436,0.0001232656,0.00007791388,0.9706755,0.0002725339,0.008769948,0.0004036,0.00001744067],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784963,0.0002386008,0.01945537,0.0005153778,0.00002158106,0.00001301615,0.0002266401,0.00005236139,0.000980792],"genre_scores_gemma":[0.9968965,0.0001539066,0.001649097,0.000111266,0.00001067418,0.00001736157,0.0001046048,0.00001141068,0.001045181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01034915,"threshold_uncertainty_score":0.02057785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01130386055120577,"score_gpt":0.3247589104126301,"score_spread":0.3134550498614244,"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."}}