{"id":"W4205534036","doi":"10.3390/v14020177","title":"Identifying Inhibitors of −1 Programmed Ribosomal Frameshifting in a Broad Spectrum of Coronaviruses","year":2022,"lang":"en","type":"article","venue":"Viruses","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Research Council Canada; National Institutes of Health; Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Translational frameshift; Coronavirus disease 2019 (COVID-19); Broad spectrum; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Coronavirus; Biology; Virology; Computational biology; Spectrum (functional analysis); Genetics; Medicine; Chemistry; RNA; Ribosome; Gene; Physics; Outbreak","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002212218,0.0005400924,0.0004794851,0.0004079733,0.0001506244,0.0003366088,0.0002399986,0.0002932014,0.0007997691],"category_scores_gemma":[0.0001332848,0.0002331307,0.0003159227,0.0001829267,0.0001567968,0.0002027881,0.0001823948,0.0004647111,0.0002267502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003150672,"about_ca_system_score_gemma":0.0002216105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006283467,"about_ca_topic_score_gemma":0.003129888,"domain_scores_codex":[0.9999263,0.00001202199,0.000008471461,0.00001367099,0.00002164625,0.00001781892],"domain_scores_gemma":[0.9999386,0.00001482717,0.00001502376,0.000004280527,0.00001264252,0.00001460508],"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":[0.0003205553,0.0002713084,0.0006622045,0.0001371338,0.00003302941,0.0001095834,0.00003219169,0.001021724,0.9844694,0.0002144687,0.00014559,0.012583],"study_design_scores_gemma":[0.0005236433,0.007503127,0.008304683,0.00005587846,0.000154305,0.0007643298,0.0000477623,0.003190274,0.9682745,0.0001522381,0.0109992,0.00003006464],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741641,0.01699451,0.003400418,0.0001730557,0.00005885175,0.0002225216,0.0003833855,0.0001285844,0.004474449],"genre_scores_gemma":[0.9809884,0.01097209,0.003931371,0.0001345579,0.00002926499,0.000129222,0.0007528434,0.00001760778,0.003044622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007997691,"threshold_uncertainty_score":0.002675533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02768938723456271,"score_gpt":0.2816952107820976,"score_spread":0.2540058235475349,"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."}}