Host-Parasite Interactions between Birds and Feather Mites
Bibliographic record
Abstract
There is current uncertainty on whether feather mites are a cause or consequence of poor body condition in birds. We aimed at investigating the bird-mite relationships and elucidating the functional significance of feather mites on birds found on the Urra Field station, Sorbas, in Almeria province, south-east Spain. We captured birds using mist nest and assessed birds for body condition (weight, fat and pectoral muscles), mite distribution on the wings and tested for diurnal changes in mite abundance. The Kruskal-Wallis test was used to test for differences in mite abundance across species, sex, age and to test for differences in mite distribution on wings across species while the Fisher`s exact test was used to test for diurnal mite abundance. There were no significant differences in mite abundance between males and females in blackcaps, house sparrows, Sardinian and Willow warblers. There were significant differences in the abundance of mites on Blackcaps, house sparrows, sardinian and willow warblers. This study was carried out just before the breeding season, thus the juveniles may have been “mite-contaminated” by adults during the winter. Also, blackcaps could potentially be carrying different mite species, collected enroute during their migration. With more observational data over different time of day and seasons, investigations could be carried out to describe mite movements depending on varying environmental factors.
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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".