Ectoparasites, nestling growth, parental feeding rates, and begging intensity of tree swallows
Bibliographic record
Abstract
Many studies fail to show relationships between ectoparasite loads and nestling growth rates. One explanation is that parent birds increase feeding rates to compensate for nestling energetic losses to ectoparasites. Nestling begging behaviours could signal need to parents. Accordingly, we tested whether higher flea and blow fly loads in tree swallow (Tachycineta bicolor) nests were associated with smaller nestlings, higher parental feeding rates, and increased nestling begging intensity. The study area was the Gaspereau Valley of Nova Scotia, Canada. When nestlings were 10 days old, parental feeding rates and nestling begging intensity were measured with tape recorders. At 13 days of age, nestlings were weighed and measured. Within 2 days of fledging, nest material was removed from nest boxes and enumerated for adult fleas and blow fly pupae. After including brood size and date of first egg as covariates in general linear models, no significant relationships were found between ectoparasite loads and nestling size, parental feeding rate, or nestling begging intensity. Our results suggest that nestling tree swallows were able to buffer the effects of naturally occurring ectoparasite loads without significant help from their parents. Low levels of virulence may have resulted from relatively benign weather during the study, low numbers of ectoparasites, selection on ectoparasites to avoid killing their hosts, and host defences.
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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) | 0.001 | 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".