{"id":"W4296690243","doi":"10.1038/s41375-022-01697-9","title":"A primary hierarchically organized patient-derived model enables in depth interrogation of stemness driven by the coding and non-coding genome","year":2022,"lang":"en","type":"article","venue":"Leukemia","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"Canadian Institutes of Health Research; Princess Margaret Cancer Foundation","keywords":"Computational biology; Biology; Epigenetics; Myeloid leukemia; Stem cell; CRISPR; Population; Cancer stem cell; Genome editing; Genetics; Cancer research; Gene; 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":[0.0001180715,0.0003087025,0.0003129826,0.0001943447,0.0001776303,0.0004521746,0.0004083235,0.0004122693,0.001986897],"category_scores_gemma":[0.0002033851,0.0001538853,0.000484467,0.000162014,0.0002704645,0.0001921007,0.0002954606,0.000562697,0.0004491951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004797939,"about_ca_system_score_gemma":0.0008528169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003576229,"about_ca_topic_score_gemma":0.003455684,"domain_scores_codex":[0.9999325,0.00001239403,0.000003058547,0.0000240694,0.00001651026,0.00001138932],"domain_scores_gemma":[0.9999338,0.00001881272,0.00001233319,0.00001288387,0.000008929368,0.0000132606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002413333,0.000237988,0.00537632,0.0002057225,0.0000693273,0.0004877857,0.00008979991,0.5936342,0.3653122,0.01907803,0.00191397,0.01335333],"study_design_scores_gemma":[0.00005482371,0.0002769763,0.002544032,0.00001234695,0.00004928451,0.0002923841,0.00004574777,0.9392584,0.04252989,0.006650383,0.008261162,0.00002460209],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5347108,0.0006408442,0.442648,0.0007626938,0.0001028885,0.0001971622,0.006872327,0.00118872,0.01287656],"genre_scores_gemma":[0.9315942,0.0004978749,0.06037904,0.0001268277,0.00001546005,0.0002229924,0.002997283,0.0001038718,0.004062469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003576229,"threshold_uncertainty_score":0.007110834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493931796472892,"score_gpt":0.2476150822208278,"score_spread":0.2326757642560989,"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."}}