Host sex and parasitism in Red-winged Blackbirds (<i>Agelaius phoeniceus</i>): examining potential causes of infection biases in a sexually dimorphic species
Bibliographic record
Abstract
Sex biases in parasitism rates are widely reported in the literature. Among vertebrates in particular, males are more frequently parasitized than females. These sex-linked differences are often attributed to different investment strategies in current versus future reproduction at the ultimate level and to different levels of circulating androgens at the proximate level. But there are other factors that can influence parasitism rates that are often neglected. In this study, we examined multiple measures of parasitism in male and female Red-winged Blackbirds (Agelaius phoeniceus (L., 1766)) to determine whether sex biases occur and sought to identify physiological and ecological factors that may be shaping such differences. We assessed three groups of parasites (ectoparasites, intestinal parasites, blood parasites), one measure of immune function (bacteria-killing ability), and diet. We found that male-biased infections were common only for intestinal parasites, but could not be attributed to dietary or immunological differences. We also found that immune function was associated with an individual’s infection status, appearing elevated in males infected with helminths. Our results suggest that, for this species, sex biases in parasitism do occur but are not the norm. Furthermore, their existence may depend on the nature of the host–parasite relationship.
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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".