Plant Virus RNAs. Coordinated Recruitment of Conserved Host Functions by (+) ssRNA Viruses during Early Infection Events
Bibliographic record
Abstract
Positive-sense single-stranded RNA viruses have developed strategies to exploit cellular resources at the expense of host mRNAs. The genomes of these viruses display a variety of structures at their 5' and 3' ends that differentiate them from cellular mRNAs. Despite this structural diversity, viral RNAs are still circularized by juxtaposition of their 5' and 3' ends, similar to the process used by cellular mRNAs. Also reminiscent of the mechanisms used by host mRNAs, translation of viral RNAs involves the recruitment of translation initiation factors. However, the roles played by these factors likely differ from those played by cellular mRNAs. In keeping with the general parsimony typical of RNA viruses, these host factors also participate in viral RNA replication. However, the dual use of host factors requires that viral RNA template utilization be regulated to avoid conflict between replication and translation. The molecular composition of the large ribonucleoprotein complexes that form the viral RNA replication and translation machineries likely evolves over the course of infection to allow for switching template use from translation to replication.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".