Effects of sex and body size on ectoparasite loads in the northern flying squirrel (<i>Glaucomys sabrinus</i>)
Bibliographic record
Abstract
Ectoparasites can have profoundly negative fitness consequences for host organisms. Sex differences in parasite load have been documented in many mammals, and have been attributed either to the allocation of energy to growth rather than the immune system in mammals exhibiting male-biased sexual size dimorphism or to the immunosuppressive qualities of testosterone. In addition, ectoparasites can have negative effects on body size and condition, as energy is allocated to the immune system rather than to growth and maintenance. Here, we used the northern flying squirrel (Glaucomys sabrinus (Shaw, 1801)) and its ectoparasites to test two predictions: (1) males are more heavily parasitized than females and (2) individuals with high ectoparasite loads will be in poorer condition and be smaller than individuals with low ectoparasite loads. Males were significantly more parasitized than females, and there was a nonsignificant trend for small males to be more parasitized than large males. Because the northern flying squirrel is not sexually dimorphic, the immunosuppressive qualities of testosterone may explain the sex differences in ectoparasite load. Ectoparasites may also influence skeletal growth rates, and males that are more susceptible to ectoparasites may simply be unable to allocate as much energy to growth and are thus structurally smaller.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".