Bibliographic record
Abstract
Interest in parasites of wildlife has increased significantly in recent years. Pleasingly, the role of wildlife as the source of emerging infectious diseases has been countered by reasoned and balanced responses from ecologists and conservationists concerned about the dearth of knowledge of the infectious agents harboured by wildlife, their impact on wildlife health, the factors, both natural and anthropogenic, that might cause perturbations in the host–parasite relationships, and the need for ongoing surveillance of wildlife populations. In essence, wildlife should be seen as a critical component of the One Health triad on an equal footing to humans and domestic animals – not just a source of disease. In its short history, we hope that International Journal for Parasitology: Parasites and Wildlife has contributed to this re-positioning of wildlife within One Health by promoting the broad scope of wildlife parasitology through the diversity of papers published to date. We were therefore delighted to accept an invitation to be joint editors of a special issue of Trends in Parasitology on wildlife parasitology. A series of broad-ranging reviews and opinion articles was solicited to provide the broad parasitological community with an insight into both neglected and emerging areas of wildlife parasitology, as well as fields in need of rejuvenation. We hope this will help to stimulate research on wildlife parasitology, especially by the development of multidisciplinary groups, and importantly direct authors to seek a dedicated forum for publishing their findings – International Journal for Parasitology: Parasites and Wildlife.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.041 | 0.017 |
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".