Building RNA Backbone in Constant Time by Numerical Approximation
Bibliographic record
Abstract
We present a numerical approximation method designed to swiftly create RNA ribose conformations in constant time. The method’s parameterization relies on the atomic coordinates of a given base along with its two neighboring phosphate groups. Such a parameterization suits three dimensional modeling engines that determine the RNA conformational search space using base operations instead of backbone sampling. These engines consider phosphate groups as part of the base rigid bodies. Reconstructing ribose conformations result in less than 1 Å of RMSD (root-mean-square deviation) compared to original conformations derived from high-resolution X-ray crystallographic structures. By incorporating this ribose construction method into MC-Sym , a well-established RNA three dimensional modeling software, we streamline the modeling process into two phases. This enhances the search algorithm’s speed and improves model consistency and precision. Additionally, we employed the method to pinpoint 27 irregular ribose stereoisomers in high-resolution RNA X-ray crystal structures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".