Bibliographic record
Abstract
Members of the family Dicistroviridae are small RNA viruses containing a monopartite positivesense RNA genome.Dicistroviruses mainly infect arthropods, causing diseases that impact agriculture and the economy.In this chapter, we provide an overview of current and past research on dicistroviruses including the viral life cycle, viral translational control mechanisms, virus structure, and the use of dicistrovirus infection in Drosophila as a model to identify insect antiviral responses.We then delve into how research on dicistrovirus mechanisms has yielded insights into ribosome dynamics, RNA structure/function and insect innate immunity signalling.Finally, we highlight the diseases caused by dicistroviruses, their impacts on agriculture including the shrimp and honey bee industries, and the potential use of dicistroviruses as biopesticides.Although knowledge of the mechanisms underlying dicistrovirus virus-host interactions is limited, the establishment of the first infectious clone should accelerate the discovery of new mechanistic insights into dicistrovirus infections and pathogenesis. 1A2B 2C 3A 3C
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".