Risk of parasite-induced predation: an experimental field study on Townsend's voles (<i>Microtus townsendii</i>)
Bibliographic record
Abstract
Studies of causes of mortality in rodents, snowshoe hares, and red grouse show that many individuals succumb to predation and few die from starvation or parasite infestation. Predation may be the proximate cause of death and factors like parasite infestation and starvation could facilitate predation. Our aim was to test whether Townsend's voles, Microtus townsendii, experimentally rid of parasites are less likely to be killed by predators than are control voles. During two breeding seasons we treated half of the adults caught at Boundary Bay, British Columbia, Canada, with the anthelmintic Ivomec® and left the other half as controls. Voles were randomly assigned to the treatment and control groups. Predators killed 5 of 23 treated voles and 11 of 26 control voles in 1998. In 1997 predators killed 3 of 17 treated voles and 2 of 18 control voles. Vole density was higher in 1998 than in 1997 and predation was the main cause of mortality in both years. Survival of control voles was lower in 1998 than in 1997, indicating lower predation pressure in 1997 than in 1998. Botfly prevalence and intensity were low and similar in both years. We speculate that the lack of treatment effect in 1997 could have been due to lower overall parasite prevalence in that year than in 1998, resulting in relatively higher susceptibility of voles to predation. Parasite-induced predation reduced monthly survival by 17% in 1998.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".