{"id":"W3011957110","doi":"10.1016/j.celrep.2020.02.048","title":"Genomic Repeats Categorize Genes with Distinct Functions for Orchestrated Regulation","year":2020,"lang":"en","type":"article","venue":"Cell Reports","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":172,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Key Research and Development Program of China; National Institute of General Medical Sciences; Medical Research Council; National Institutes of Health; Tsinghua University; Center for Life Sciences; University of Toronto; National Natural Science Foundation of China; UK Research and Innovation","keywords":"Biology; Gene; Genetics; Genome; Gene silencing; Regulation of gene expression; Computational biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000100332,0.00009683242,0.00009185094,0.00001413977,0.0001030599,0.00002726325,0.00004721778,0.00006520814,0.00001652517],"category_scores_gemma":[0.00005352935,0.00008090083,0.0000497978,0.00007065649,0.00003312734,0.000003149675,0.00002793548,0.00004630463,0.000003894752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001232463,"about_ca_system_score_gemma":0.0001502437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002200552,"about_ca_topic_score_gemma":0.00001791215,"domain_scores_codex":[0.9991792,0.00001655323,0.0001779497,0.0003514853,0.00008846272,0.0001863348],"domain_scores_gemma":[0.9994063,0.000007433244,0.0001003427,0.0002438167,0.0001067038,0.0001354001],"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":[0.0001386131,0.0000157837,0.01010809,0.00003041363,0.00001935888,0.00003955846,0.00001333717,0.0003293256,0.9863647,0.000003025804,0.0021175,0.0008202714],"study_design_scores_gemma":[0.0005419474,0.0008846425,0.01896425,0.000006906253,0.00004043583,0.0001411684,0.00008095493,0.001046263,0.9221572,0.00005044679,0.0558157,0.0002701005],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791245,0.0002519141,0.01861813,0.0001730904,0.00004776039,0.0003108457,0.000005419063,0.00002088846,0.001447451],"genre_scores_gemma":[0.9920898,0.00001565534,0.0007042088,0.00005326996,0.0002432781,0.0000452617,0.0004611352,0.00002252371,0.006364839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06420754,"threshold_uncertainty_score":0.329904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02016885232201882,"score_gpt":0.2426902220134007,"score_spread":0.2225213696913819,"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."}}