{"id":"W2907714971","doi":"10.1182/blood-2018-99-116241","title":"Identification of High Risk Group for Leukemic Transformation in Higher Risk MDS Patients Using Targeted RNA-Sequencing: Hematopoietic Stem Cell Signature As a High Risk Profile for Leukemic Transformation","year":2018,"lang":"en","type":"article","venue":"Blood","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Princess Margaret Cancer Centre; Occupational Cancer Research Centre; University of Toronto","funders":"","keywords":"Decitabine; Oncology; Azacitidine; Internal medicine; Myelodysplastic syndromes; Leukemia; Myeloid; Myeloid leukemia; Bone marrow; International Prognostic Scoring System; Medicine; Biology; Bioinformatics; Computational biology; Gene; Genetics; DNA methylation; Gene expression","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":[0.0001998122,0.0002307103,0.0003369244,0.000741023,0.000283231,0.0004497375,0.0001292989,0.0002288274,0.001870582],"category_scores_gemma":[0.0003517057,0.00008618513,0.0002269559,0.0005299038,0.0001508111,0.0001168913,0.0002531805,0.0002351567,0.0003376258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001363797,"about_ca_system_score_gemma":0.0001609763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003154811,"about_ca_topic_score_gemma":0.0005097181,"domain_scores_codex":[0.9998401,0.00002418593,0.00001953972,0.00005508323,0.00003608398,0.00002488877],"domain_scores_gemma":[0.999854,0.00002815417,0.0000511186,0.00001166096,0.0000278815,0.00002722121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001268077,0.0001011792,0.8483393,0.0001412808,0.0001039389,0.0008207688,0.0002948153,0.0006223649,0.1205241,0.0002470302,0.0007908242,0.02674635],"study_design_scores_gemma":[0.00005882632,0.0005645795,0.9555144,0.00004381226,0.0002359507,0.003344432,0.0004363386,0.004528074,0.02987403,0.0007694213,0.004601427,0.00002862797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963799,0.000548258,0.001532808,0.00006080057,0.0000115178,0.00003878969,0.0008635065,0.00003047423,0.0005338834],"genre_scores_gemma":[0.9963036,0.000210848,0.001656326,0.00005529663,0.00001869119,0.00004426929,0.001228334,0.000008378453,0.0004744212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001870582,"threshold_uncertainty_score":0.006257713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01856404663727402,"score_gpt":0.2625520511501162,"score_spread":0.2439880045128421,"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."}}