Negative covariance between parasite load and body condition in a population of feral horses
Bibliographic record
Abstract
In wild and domestic animals, gastrointestinal parasites can have significant impacts on host development, condition, health, reproduction and longevity. Improving our understanding of the causes and consequences of individual-level variation in parasite load is therefore of prime interest. Here we investigated the relationship between strongyle fecal egg count (FEC) and body condition in a unique, naturalized population of horses that has never been exposed to anthelmintic drugs (Sable Island, Nova Scotia, Canada). We first quantified variation in FEC and condition for 447 individuals according to intrinsic (sex, age, reproductive status, social status) and extrinsic (group size, location, local density) variables. We then quantified the repeatability of measurements obtained over a field season and tested for covariance between FEC and condition. FECs were high relative to other horse populations (mean eggs per gram ± SD = 1543·28 ± 209·94). FECs generally decreased with age, were higher in lactating vs non-lactating females, and unexpectedly lower in males in some part of the island. FECs and condition were both spatially structured, with patterns depending on age, sex and reproductive status. FECs and condition were both repeatable. Most notably, FECs and condition were negatively correlated, especially in adult females.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".