{"id":"W2969991859","doi":"10.1016/j.exphem.2019.06.405","title":"INTEGRATIVE EPIGENOMIC ANALYSIS TO IDENTIFY POTENTIAL BIOMARKERS IN KMT2A TRANSLOCATED ACUTE MYELOID LEUKEMIA","year":2019,"lang":"en","type":"article","venue":"Experimental Hematology","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"","keywords":"Epigenomics; Myeloid leukemia; Biology; Computational biology; Myeloid; Leukemia; Cancer research; DNA methylation; Genetics; Gene","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":[0.0003000729,0.0002799792,0.0003906154,0.0008966326,0.0002415919,0.0005089578,0.0002412836,0.0002342053,0.002219962],"category_scores_gemma":[0.0003456243,0.0001375309,0.0003619834,0.0008234701,0.0001421589,0.0002321202,0.0005189142,0.0003935077,0.0002944834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002182287,"about_ca_system_score_gemma":0.000281214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005570719,"about_ca_topic_score_gemma":0.001197757,"domain_scores_codex":[0.9998016,0.00002171351,0.00001256603,0.00007092216,0.00005360776,0.00003968638],"domain_scores_gemma":[0.9998719,0.00002975191,0.00004519049,0.00001441478,0.00002214367,0.00001667398],"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":[0.001002402,0.000095056,0.04909748,0.0003047431,0.0003190986,0.0004692742,0.000158582,0.0009282526,0.9056634,0.0008511664,0.0009627601,0.04014766],"study_design_scores_gemma":[0.0002180623,0.0009262757,0.651917,0.0001218145,0.002151894,0.003865883,0.0007997517,0.02417015,0.2650223,0.003219565,0.04751068,0.0000766435],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788359,0.002778473,0.009793213,0.0002146055,0.00005278398,0.00007245287,0.005761343,0.0001674764,0.002323858],"genre_scores_gemma":[0.982979,0.001100505,0.006443551,0.000204363,0.00002973729,0.00008140962,0.007133396,0.00005492273,0.001973105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002219962,"threshold_uncertainty_score":0.00742656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213253589279873,"score_gpt":0.3434443823308263,"score_spread":0.3313118464380276,"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."}}