{"id":"W3159478241","doi":"10.1261/rna.078747.121","title":"Differential translation of mRNA isoforms transcribed with distinct sigma factors","year":2021,"lang":"en","type":"article","venue":"RNA","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Searle Scholars Program; Howard Hughes Medical Institute; National Institutes of Health; National Science Foundation","keywords":"Sigma factor; Biology; Regulon; RNA polymerase; Genetics; Transcription (linguistics); Promoter; Eukaryotic translation; RNA; Translation (biology); Gene; Cell biology; Transcription factor; Molecular biology; Gene expression; Messenger RNA","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003224336,0.0001073323,0.0001342902,0.00001439589,0.00003820317,0.000009900207,0.00007516887,0.00008819104,0.0001789795],"category_scores_gemma":[0.000009601983,0.00007862577,0.0000893488,0.00005123124,0.00002901511,0.000002982558,0.000008551317,0.00003567533,0.000001052601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002994225,"about_ca_system_score_gemma":0.00003836791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001294353,"about_ca_topic_score_gemma":0.00004399059,"domain_scores_codex":[0.9993939,0.00003358158,0.0001443408,0.0001842866,0.000117221,0.0001266654],"domain_scores_gemma":[0.9996691,0.000007964946,0.00005289086,0.0001843219,0.00004295547,0.00004276565],"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":[0.0001183012,0.00004600723,0.000677721,0.00002555874,0.00005769452,0.000002759187,0.00009184008,0.000004963727,0.9899886,0.00005416956,0.000008657861,0.008923692],"study_design_scores_gemma":[0.0003325907,0.000186036,0.003290091,0.00001930895,0.00003807202,0.000004643999,0.0000609598,0.00001233072,0.995056,0.0001010702,0.0007825654,0.0001163686],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9562335,0.0002213612,0.0424645,0.00005063976,0.00006532431,0.0000888442,0.00002939741,0.000007070229,0.0008393515],"genre_scores_gemma":[0.9987285,0.00003038283,0.0007332843,0.00001026102,0.00005700636,0.000006241733,0.0001465309,0.00001545986,0.0002724001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04249492,"threshold_uncertainty_score":0.3206266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412995933591131,"score_gpt":0.2214950778254521,"score_spread":0.2073651184895408,"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."}}