{"id":"W4296456774","doi":"10.1038/s41467-022-33244-6","title":"Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"Hyundai Hope On Wheels; Children’s Oncology Group; St. Baldrick's Foundation; Fred Hutchinson Cancer Research Center; Rally Foundation; Office of Research Infrastructure Programs, National Institutes of Health; Leukemia and Lymphoma Society; National Cancer Institute; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Myeloid leukemia; Risk stratification; Oncology; Medicine; Biomarker; Predictive power; Leukemia; Cohort; Internal medicine; Population; Myeloid; Bioinformatics; Computational biology; Biology; Genetics","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":[0.00109013,0.000378765,0.0004257454,0.0008458489,0.0001332487,0.000700625,0.000353731,0.0002942703,0.0009834161],"category_scores_gemma":[0.002391751,0.0001312871,0.0003309674,0.0007979122,0.0002071005,0.0003121673,0.0007423925,0.0004846544,0.0003903587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003407786,"about_ca_system_score_gemma":0.0005251549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001258014,"about_ca_topic_score_gemma":0.002389239,"domain_scores_codex":[0.9995821,0.0001319525,0.00003051345,0.0000939169,0.000117602,0.00004389953],"domain_scores_gemma":[0.9991515,0.0002409325,0.0003185405,0.0001057124,0.000096703,0.00008663665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006179531,0.00006637219,0.9259628,0.00004470341,0.0001814614,0.0001564562,0.00007688691,0.01286975,0.01012741,0.0003200568,0.0005730632,0.04900303],"study_design_scores_gemma":[0.00006583182,0.0006692138,0.8049663,0.00006044612,0.0004201642,0.001196135,0.0002328572,0.1579677,0.02713476,0.002818584,0.004430683,0.00003723431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917971,0.0004294481,0.006344792,0.00009774901,0.000006066697,0.00002209548,0.0007818183,0.0001020519,0.0004188807],"genre_scores_gemma":[0.9929793,0.0001602224,0.00503328,0.00004390437,0.00001521169,0.00002281373,0.001559492,0.00001628805,0.0001693952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001258014,"threshold_uncertainty_score":0.0057652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01265809859795216,"score_gpt":0.2892729242019716,"score_spread":0.2766148256040195,"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."}}