Bibliographic record
Abstract
▪ Abstract Baculoviruses occur widely among Lepidoptera, and in some species of forest and agricultural insects, they cause epizootics in outbreak populations. Here we review recent developments in baculovirus ecology and evolution, in particular focusing on emerging areas of interest and studies relating to field populations. The expanding application of molecular techniques has started to reveal the structure of baculovirus populations and has highlighted how variable these pathogens are both genotypically and phenotypically at all levels from within individual hosts to among host populations. In addition, the detailed molecular knowledge available for baculoviruses has allowed the interpretation of gene functions across physiological and population levels in a way rarely possible in parasite-host systems and showed the diverse mechanisms that these viruses use to exploit their hosts. Analysis of the dynamic interactions between insects and baculoviruses, and their compatibility for laboratory and field experiments, has formed a basis for studies that have made a significant contribution to unraveling disease interactions in insect populations. In particular, manipulative studies on baculoviruses have been instrumental in developing an understanding of disease transmission dynamics. The results so far indicate that baculoviruses have the potential to be an excellent model for investigations of changes in virulence and resistance in fluctuating and stable host populations.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".