Bibliographic record
Abstract
The term “RNA editing” was first coined more than a decade ago to describe the phenomenon of uridine insertion into trypanosomatid mitochondrial transcripts. Unlike mRNAs, transcripts of tRNA and rRNA genes are themselves converted into the functional entities they encode. RNA editing events represent additional steps in posttranscriptional processing and, like nucleoside modifications, they may occur at different stages in the pathway. To quantify RNA editing one usually compares the intensity of the bands on a sequencing (or primer extension) ladder that correspond to the edited and unedited versions of the RNA. The first example of tRNA editing in a mitochondrial (mt) system is that reported to occur in the ameboid protozoon Acantbamoeba castellanii. The observed nucleotide substitutions consisted of both purine-to-purine and pyrimidine- to-purine changes, suggesting a mechanism involving base or nucleotide replacement. More recently, it has been shown that nascent mRNAs present in stalled RNA polymerase complexes are substrates for editing by both cytidine and dinucleotide insertion. In a particular study the isolated RNAs were found to be edited to within 14 to 22 nucleotides of the stalled polymerase, suggesting that the insertional editing activity in Physarum is able to act quite close to the site of RNA synthesis. The most recently described mode of tRNA editing is that found in the mitochondria of metazoa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.008 | 0.007 |
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".