{"id":"W2007771322","doi":"10.1038/ng.375","title":"The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line","year":2009,"lang":"en","type":"article","venue":"Nature Genetics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":430,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"U.S. National Library of Medicine; Medical Research Council; National Heart, Lung, and Blood Institute; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Ministry of Education, Culture, Sports, Science and Technology; RIKEN; National Health and Medical Research Council; Wellcome Trust","keywords":"Biology; Transcription factor; Gene knockdown; Cellular differentiation; Gene regulatory network; Transcription (linguistics); Transcriptional regulation; Cell biology; Myeloid leukemia; Regulation of gene expression; Computational biology; Cell culture; Gene; Genetics; Gene expression; Cancer research","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":[0.00005920137,0.0001163653,0.0001278893,0.0002155076,0.000199234,0.0002663498,0.000125232,0.0001205464,0.0007403073],"category_scores_gemma":[0.0001119032,0.0001365924,0.0001118549,0.0001906584,0.0001422359,0.0001382482,0.0001045353,0.0002420311,0.0003597116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003430924,"about_ca_system_score_gemma":0.0001929282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001797369,"about_ca_topic_score_gemma":0.002692174,"domain_scores_codex":[0.9999382,0.000006767574,0.000003420001,0.00001791737,0.00001905883,0.00001449647],"domain_scores_gemma":[0.9999312,0.00001393902,0.0000144228,0.00001186937,0.00001037383,0.00001814405],"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":[0.00005887381,0.000006189232,0.0004861104,0.000004440616,0.00000161554,0.00002182873,0.000008980426,0.0001465324,0.9983984,0.0002492189,0.00003541153,0.000582373],"study_design_scores_gemma":[0.00002427369,0.0001230468,0.03553132,0.000004668761,0.00001713558,0.000251905,0.00005055802,0.004044284,0.9564739,0.0003813833,0.003092234,0.000005364377],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944318,0.0004210042,0.002403148,0.0001247271,0.000009056937,0.00001039061,0.0007522488,0.00008016517,0.001767491],"genre_scores_gemma":[0.9963803,0.0001722717,0.000859723,0.0000311695,0.000005205768,0.00001047255,0.0008167149,0.00001755428,0.001706546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001797369,"threshold_uncertainty_score":0.003573835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003938502606471444,"score_gpt":0.20716260068945,"score_spread":0.2032240980829785,"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."}}