{"id":"W2989998760","doi":"10.1038/s41467-019-13228-9","title":"Poly(A) inclusive RNA isoform sequencing (PAIso−seq) reveals wide-spread non-adenosine residues within RNA poly(A) tails","year":2019,"lang":"en","type":"article","venue":"Nature Communications","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Department of Science and Technology for Social Development; Ministry of Science and Technology of the People's Republic of China; Chinese Academy of Sciences; Institute of Genetics; National Natural Science Foundation of China","keywords":"Gene isoform; RNA; Messenger RNA; Complementary DNA; Adenosine; Function (biology); Biology; Computational biology; Molecular biology; Cell biology; Gene; Chemistry; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003389356,0.0003134661,0.0002669694,0.0002902488,0.0002727547,0.0005453692,0.0002827192,0.000397268,0.0009298535],"category_scores_gemma":[0.0005842333,0.0001872951,0.0002450403,0.0003186897,0.0002756868,0.0002776318,0.0002989852,0.0007508984,0.0006533988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001530257,"about_ca_system_score_gemma":0.0002184586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004805907,"about_ca_topic_score_gemma":0.001866223,"domain_scores_codex":[0.9996815,0.00003246552,0.00001806878,0.0001447603,0.00009949162,0.00002367622],"domain_scores_gemma":[0.9994667,0.0001571137,0.000157082,0.00007929053,0.00008572925,0.0000540665],"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":[0.00002864694,0.00000502185,0.0007220756,0.00004253136,0.000007887275,0.00002763725,0.00002377691,0.0001103638,0.9945822,0.0002156346,0.00014509,0.004089031],"study_design_scores_gemma":[0.0000121282,0.0001588371,0.02327071,0.00002328059,0.00003548356,0.0004137036,0.00006220554,0.006938501,0.956041,0.000904198,0.01211843,0.00002162632],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7035783,0.002576616,0.2757794,0.0003154094,0.0002456362,0.0001191508,0.007349111,0.001875789,0.008160611],"genre_scores_gemma":[0.7583275,0.003028828,0.2179902,0.001034764,0.0001426019,0.0002679719,0.009706397,0.0008399689,0.008661751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009298535,"threshold_uncertainty_score":0.003110707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01507585901613384,"score_gpt":0.3122913418036721,"score_spread":0.2972154827875382,"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."}}