Salivary cortisol is an unreliable correlate of serum cortisol in adult pet dogs and assistance dog puppies
Bibliographic record
Abstract
Cortisol is widely used in mammals as a measure of HPA axis response. To estimate response to an acute stressor, minimize pain and ease sample collection, salivary cortisol has become preferred over serum cortisol across a variety of species. This includes domestic dogs in which research with laboratory dogs initially demonstrated the predicted relationship between cortisol concentrations in serum and salivary levels sampled within minutes of each other. The Model Population Hypothesis suggests a laboratory dog should be physiologically representative of all dogs. We provide a critical test of this idea by providing the first validation of salivary cortisol against serum measures in healthy puppies less than six months of age (n = 34; 8 to 20-week-old Labrador x Golden Retrievers) as well as a group of healthy adult pet dogs (n = 38). Following previously established methodology, blood and saliva were collected within 4 min of each other. Puppies were sampled multiple times while adults were sampled once. We found that salivary and serum cortisol are poorly correlated in our puppies r(216) = - 0.092, p = 0.178, and adult dogs (r(36) = 0.092, p = 0.582). Our results suggest that previously validated methods with laboratory dogs may not translate to healthy puppies and pet dogs, particularly those less than six months of age. Further research is now needed to identify a salivary sampling method that might allow for this less invasive sampling technique to be used in puppies and pet dogs living in a range of real-world contexts.
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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 | 0.003 |
| 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 | 0.001 | 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".