Bibliographic record
Abstract
'RNA editing' describes the programmed alteration of the nucleotide sequence of an RNA species, relative to the sequence of the encoding DNA. The phenomenon encompasses two generic patterns of nucleotide change, 'insertion/deletion' and 'substitution', defined on the basis of whether the sequence of the edited RNA is colinear with the DNA sequence that encodes it. RNA editing is mediated by a variety of pathways that are mechanistically and evolutionarily unrelated. Messenger, ribosomal, transfer and viral RNAs all undergo editing in different systems, but well-documented cases of this phenomenon have so far been described only in eukaryotes, and most often in mitochondria. Editing of mRNA changes the identity of encoded amino acids and may create translation initiation and termination codons. The existence of RNA editing violates one of the long-accepted tenets of genetic information flow, namely, that the amino acid sequence of a protein can be directly predicted from the corresponding gene sequence. Particular RNA editing systems display a narrow phylogenetic distribution, which argues that such systems are derived within specific eukaryotic lineages, rather than representing traits that ultimately trace to a common ancestor of eukaryotes, or even further back in evolution. The derived nature of RNA editing raises intriguing questions about how and why RNA editing systems arise, and how they become fixed as additional, essential steps in genetic information transfer.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".