{"id":"W4200117741","doi":"10.1261/rna.078188.120","title":"The landscape of translational stall sites in bacteria revealed by monosome and disome profiling","year":2021,"lang":"en","type":"article","venue":"RNA","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; National Institutes of Health; RIKEN; Japan Agency for Medical Research and Development; Core Research for Evolutional Science and Technology; Takeda Science Foundation","keywords":"Biology; Profiling (computer programming); Stall (fluid mechanics); Bacteria; Computational biology; Evolutionary biology; Genetics; Ecology","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":[0.0001046052,0.00004957954,0.00006754787,0.00000752024,0.00002846729,0.00001184152,0.00004712373,0.00004867796,0.00001670738],"category_scores_gemma":[0.00003252493,0.00003791368,0.00002241712,0.00003178994,0.0000172468,0.000002127076,0.00001946716,0.00002458517,5.084704e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001071782,"about_ca_system_score_gemma":0.00002273496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001783534,"about_ca_topic_score_gemma":0.00001271425,"domain_scores_codex":[0.9996008,0.00004519573,0.0001100471,0.0001154813,0.0000490346,0.00007943799],"domain_scores_gemma":[0.9998133,0.00001935871,0.00003082354,0.00009798782,0.00002011559,0.00001843249],"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":[0.00003218805,0.00001252246,0.005020496,0.00001304963,0.0000103027,7.817421e-7,0.00002107461,0.000001580055,0.9926967,0.0001398292,0.00004692542,0.002004552],"study_design_scores_gemma":[0.0001779611,0.00003833831,0.005924648,0.00001095605,0.000003481205,0.000002465414,0.00004047071,0.00002891471,0.9917718,0.0005213132,0.001425276,0.00005440222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957162,0.003525329,0.0001430547,0.0002542714,0.00002060013,0.00007008448,0.00003052919,0.000001586922,0.0002384088],"genre_scores_gemma":[0.9981601,0.0005560662,0.0008686446,0.0000227863,0.00002854324,0.000009354305,0.00008017998,0.000005779477,0.0002685075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002969263,"threshold_uncertainty_score":0.1546075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007840963068940943,"score_gpt":0.2225889297968135,"score_spread":0.2147479667278725,"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."}}