Evaluating the use of salivary anti-CarLA IgA testing to reduce gastrointestinal parasitism in Canadian pastured sheep
Bibliographic record
Abstract
Gastrointestinal nematode (GIN) parasitism is common in Canadian sheep flocks, and managing GIN through the selection of sheep with superior immunity is of growing interest. The CARLA ® Saliva Test measures salivary IgA against the carbohydrate larval antigen (CarLA) found on third-stage larvae of all GIN species. Salivary anti-CarLA IgA exceeding 1.0 U/ml is associated with 20 – 30 % lower fecal egg counts (FEC) in sheep under New Zealand grazing conditions, but there has been limited application of the CARLA ® Saliva Test elsewhere. To address this gap, this study explored the utility of the CARLA ® Saliva Test under Canadian grazing conditions. In Year 1, eighteen sheep farms in Ontario were enrolled and 25 ewe lambs per farm, on average, were randomly selected after grazing pasture for at least 60 consecutive days. The body condition, fecal consistency, FAMACHA© score, weight, packed cell volume, FEC, and salivary anti-CarLA IgA level were recorded for each study animal in Year 1. Study animals returned to pasture in Year 2 and were re-sampled 4 weeks after turnout. Multivariable linear regression modeling demonstrated that the salivary anti-CarLA IgA response in Year 1 predicted the salivary anti-CarLA IgA response in Year 2 (β = 0.213; p < 0.001). In addition, salivary anti-CarLA IgA in Year 1 was negatively associated with FEC in Year 2 (β = - 0.167; p = 0.025). These data indicate that salivary anti-CarLA IgA measurements may be useful for identifying replacement sheep with superior immune responses to GIN infection in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.011 | 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 teacher head, 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".