Prediction of RNA secondary structures in SARS-CoV-2 and comparison with contemporary predictions
Bibliographic record
Abstract
A bstract SARS-CoV-2, the causative agent of covid-19, is known to exhibit secondary structure in its 5’ and 3’ untranslated regions, along with the frameshifting stimulatory element situated between ORF1a and 1b. To identify further regions containing conserved structure, multiple sequence alignment with related coronaviruses was used as a starting point from which to apply a modified computational pipeline developed to identify non-coding RNA elements in vertebrate eukaryotes. Three different RNA structural prediction approaches were employed in this modified pipeline. Forty genomic regions deemed likely to harbour structure were identified, ten of which exhibited three-way consensus substructure predictions amongst our predictive utilities. Intracomparison of the pipeline’s predictive utilities, along with intercomparison with three previously published SARS-CoV-2 structural datasets, were performed. Limited agreement as to precise structure was observed, although different approaches appear to agree upon regions likely to contain structure in the viral genome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".