Host sex and age typically explain variation in parasitism of rock ptarmigan: implications for identifying determinants of exposure and susceptibility
Bibliographic record
Abstract
Measures of parasitism often differ between hosts. This variation is thought due in part to age or sex differences in exposure to parasites and/or susceptibility to parasitism. We assessed how often age or sex biases in parasitism were found using a large, multi‐year (2006–2017) dataset of 12 parasite species of Icelandic rock ptarmigan ( Lagopus muta ). We found host traits (i.e. age and/or sex) accounted for significant variation in abundance of 11 of the 12 parasite species. We often found increased abundance among juvenile hosts, although significant adult biases were observed for three parasite species. Additionally, higher levels of parasitism by many species were observed for female hosts, contrary to frequent male biases in parasitism reported for other vertebrates. Abundance of six parasite species was best explained by interactions between host age and sex; some degree of decrease in abundance with host age was present for both male and female hosts for four of those parasite species. We consider various host and parasite traits that could account for observed singular and repeated patterns of age and/or sex biases in parasitism (e.g. age‐ and sex‐related grouping behaviours, age‐specific mortality in relation to parasitism, acquisition of greater immunity with age). This work provides a foundation for future studies investigating age‐related differences in acquired immunity and age‐specific parasite‐mediated mortality for males and females, as well as studies on interactions between co‐infecting parasite species.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".