The use of a combination of computer‐assisted structure prediction and SHAPE probing to elucidate the secondary structures of five viroids
Bibliographic record
Abstract
The elucidation of the structures of viroids, noncoding infectious RNA species, is paramount to obtain an understanding of the various aspects of their life cycles (including replication, transport and pathogenesis). In general, the secondary structures of viroids have been predicted using computer software programs which have been shown to possess several important limitations. Clearly, the predicted structure of a viroid needs to receive physical support prior to its use in the accurate interpretation of any mechanistic studies. Here, SHAPE probing coupled to computer-assisted structure prediction using the RNAstructure software program was employed to determine the structures of five viroids. These species belong to four genera of the Pospiviroidae family, and none have had their structure characterized in solution. In addition, several interesting questions were addressed by either studying various sequence variants or varying the SHAPE conditions. More importantly, this approach is novel in the study of viroids, and should be of significant aid in the determination of the structures of other RNA species.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".