Anti-parasite treatment and blood biochemistry in raptor nestlings
Bibliographic record
Abstract
We investigated the effects of parasite removal on various blood clinical–chemical variables (BCCVs). BCCVs are indicators of health, reflecting, e.g., homeostasis of liver, kidney function, and bone metabolism. The study was conducted in Norway on chicks of two predatory birds: White-tailed Eagle (Haliaeetus albicilla (L., 1758)) and Northern Goshawk (Accipiter gentilis (L., 1758)). Chicks were treated against both endoparasites (internal parasites) and ectoparasites (external parasites). We treated against ectoparasites by spraying nests with pyrethrins. Within nests, chicks were randomly treated with either an anti-helminthic medication (fenbendazole) or sterile water (controls). Treatment against either ectoparasites or endoparasites led to higher levels of the bone and liver enzyme alkaline phosphatase. Bilirubin levels were lower when treated against ectoparasites, whereas bile acids were higher. Anti-endoparasite treatment led to higher creatinine levels. In Northern Goshawks, treating against endoparasites led to higher urea levels and lower potassium levels. Treatment against ectoparasites increased uric acid and urea levels and reduced bilirubin levels and protein:creatinine ratios. In conclusion, anti-parasite treatments led to changes in several BCCVs, suggesting differences in nutrient absorption and physiological state of chicks that are possibly related to the costs of parasitism, but maybe also to the parasite treatment itself.
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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 | 0.000 | 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 | 0.001 |
| 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".