{"id":"W4322623665","doi":"10.1371/journal.pcbi.1010922","title":"Shapify: Paths to SARS-CoV-2 frameshifting pseudoknot","year":2023,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; University of Victoria; Microsoft Research","keywords":"Pseudoknot; Nucleic acid structure; Translational frameshift; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computational biology; Sequence (biology); Severe acute respiratory syndrome coronavirus; Nucleic acid secondary structure; RNA; Coronavirus disease 2019 (COVID-19); Biology; Genetics; Medicine; Gene; Ribosome","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":[0.0001993251,0.000152969,0.0001627296,0.000106729,0.0001102521,0.00002017166,0.000230914,0.0001835476,0.00002793755],"category_scores_gemma":[0.0002686858,0.0001484666,0.0000754396,0.0002157357,0.0000405173,0.000002513149,0.0001837759,0.00006876673,0.0007592177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009690715,"about_ca_system_score_gemma":0.00005611613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007107206,"about_ca_topic_score_gemma":0.000004006133,"domain_scores_codex":[0.9988287,0.0001059529,0.0002173628,0.0004285909,0.0001099172,0.0003094477],"domain_scores_gemma":[0.99951,0.00008899638,0.00006074023,0.0001851408,0.00009606598,0.00005904776],"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":[0.00003411087,0.00002910266,0.0005210591,0.000008193766,0.00005231852,0.000003989798,0.0000503831,0.000572878,0.9880324,0.003030871,0.002417907,0.005246781],"study_design_scores_gemma":[0.0003089034,0.0004412852,0.001785904,0.00002029943,0.00001185718,0.00001213059,0.00003512416,0.002258745,0.9494718,0.02183769,0.02345849,0.0003577532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978036,0.00008878737,0.0192032,0.001334617,0.000214342,0.0002499986,0.00005938725,0.00009435364,0.0007193306],"genre_scores_gemma":[0.9853707,0.00001223746,0.01108453,0.002536243,0.000312015,0.00007978064,0.000451902,0.00002786024,0.0001247385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0385606,"threshold_uncertainty_score":0.975846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04124083142538079,"score_gpt":0.3031411990622938,"score_spread":0.2619003676369129,"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."}}