Sex-biased parasitism in Richardson’s ground squirrels (<i>Urocitellus</i><i>richardsonii</i>) depends on the parasite examined
Bibliographic record
Abstract
Sex-biased parasitism is found in many species, but the skew to one sex or the other varies and is most likely due to differences in host and parasite behaviour and the intensity of sexual selection. We examined sex-biased parasitism in Richardson’s ground squirrels (Urocitellus richardsonii (Sabine, 1822)) and hypothesized that males would be more heavily parasitized than females, as they are larger, have larger home ranges, and display high aggression and fighting during the short mating season, suggesting that they may trade off investment in immunity for higher investment in reproduction. Squirrels were caught during the mating season and examined for endoparasites and ectoparasites. Body mass, condition, and immune measures were recorded. Males had higher nematode prevalence and abundance, whereas females had higher flea prevalence. Males also had lower lymphocytes than females, as well as higher neutrophil to lymphocyte ratios. Females had higher eosinophils and they were in poorer body condition than males. The higher endoparasite loads in males suggests that they may be trading off immunity, whereas higher flea prevalence in females may be due to differences in sociality between the sexes. Our study demonstrates the importance of examining multiple parasite types to understand the factors influencing sex-biased parasitism.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".