Bibliographic record
Abstract
Viruses maintain compact genomes that must be packaged within capsids typically less than 200 nanometers in diameter. Therefore, instead of coding for a full set of genes needed for replication, viruses have evolved remarkable strategies for co-opting the host cellular machinery. Additionally, viruses often increase the coding capacity of their own genomes by employing overlapping open reading frames (ORFs). Some overlapping viral ORFs involve recoding events that are programmed by the viral RNA. During these programmed recoding events, the ribosome is directed to translate in an alternative reading frame. Here we describe how the Dicistroviridae family of viruses utilize an internal ribosome entry site (IRES) in order to recruit ribosomes to initiate translation at a non-AUG codon. The IRES accomplishes this in part by mimicking the structure of a tRNA. Recently, we showed that the Israeli Acute Paralysis Virus (IAPV) member of the Dicistroviridae family utilizes its IRES to initiate translation in 2 different reading frames. Thus, IAPV has evolved an apparently novel recoding mechanism that reveals important insights into translation. Finally, we compare the IAPV structure to other systems that utilize tRNA mimicry in translation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.002 | 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".