{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001148123,0.000146652,0.000111688,0.00001855107,0.0001544639,0.00005683651,0.0001663665,0.0003298401,0.000001581752],"category_scores_gemma":[0.0000100702,0.0001184928,0.00005082761,0.00005294831,0.00004299097,0.000001781186,0.00002829292,0.0002721307,4.226864e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002493795,"about_ca_system_score_gemma":0.00003241966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001668202,"about_ca_topic_score_gemma":0.0001229735,"domain_scores_codex":[0.999204,0.00003695087,0.0001753129,0.0002330538,0.0001154298,0.0002351969],"domain_scores_gemma":[0.9996278,0.00001286311,0.00007345689,0.0001887684,0.00004704989,0.00005010559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00009196711,0.00006681729,0.01864737,0.00001751047,0.00003009904,0.000002474406,0.00006520563,0.002562531,0.9732422,0.001630856,0.000711277,0.002931745],"study_design_scores_gemma":[0.003076733,0.0006511112,0.8800348,0.00002900124,0.00006128307,0.00001204442,0.00006219964,0.009396945,0.08027689,0.01489237,0.01095221,0.0005544286],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887356,0.009637726,0.0006303356,0.0003222526,0.0001991308,0.0001818396,0.00001465753,0.000005617503,0.0002728721],"genre_scores_gemma":[0.9954224,0.002750883,0.0005717503,0.0004836487,0.0004276257,0.000006571076,0.0001878042,0.00001346246,0.0001359061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8929653,"threshold_uncertainty_score":0.4831995,"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."}}