{"id":"W4391743314","doi":"10.1101/2024.02.09.579319","title":"Identification of leukemia stem cell subsets with distinct transcriptional, epigenetic and functional properties","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"Government of Ontario; Princess Margaret Cancer Foundation; Celgene","keywords":"Epigenetics; Biology; Myeloid leukemia; Stem cell; Compartment (ship); Leukemia; Somatic evolution in cancer; Computational biology; Cell; Genetic heterogeneity; Cancer research; Genetics; Cancer; Gene; Phenotype","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":[0.0002297458,0.0001862799,0.0002938708,0.0004855241,0.0001518412,0.0006421354,0.000111268,0.0002282452,0.002234982],"category_scores_gemma":[0.0001671651,0.000088278,0.0001688664,0.0002316851,0.0002309749,0.0001909466,0.0002938986,0.000442505,0.0007192457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002107442,"about_ca_system_score_gemma":0.0001446166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002614666,"about_ca_topic_score_gemma":0.0003557449,"domain_scores_codex":[0.9998776,0.00001223052,0.00001031559,0.00003971309,0.00003632654,0.00002379263],"domain_scores_gemma":[0.999887,0.00002264575,0.00002075754,0.00001845899,0.00002227256,0.00002884715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000185568,0.00002277147,0.004190494,0.00002929899,0.000005768295,0.00004110326,0.00005339451,0.00009502465,0.9904862,0.0002968511,0.0001413285,0.004452127],"study_design_scores_gemma":[0.00003513002,0.0002938854,0.04210609,0.00001731101,0.0000283553,0.000638677,0.0002118777,0.003332053,0.9425952,0.0005706672,0.01015978,0.00001092666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865584,0.0008158713,0.008934657,0.0001360762,0.00002005971,0.00005848744,0.001579914,0.0001634281,0.001733167],"genre_scores_gemma":[0.9884455,0.0003231731,0.006334873,0.00009485609,0.00001548107,0.0000711964,0.002192543,0.00004392223,0.00247845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002234982,"threshold_uncertainty_score":0.007476807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02347091997146641,"score_gpt":0.2243197882332178,"score_spread":0.2008488682617514,"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."}}