Histomorphology of sweat glands in different breeds of dogs
Bibliographic record
Abstract
This study examined the histomorphology of sweat glands across various dog breeds, focusing on their structural characteristics and adaptations to environmental needs. Skin samples from 48 dogs representing indigenous and seven breeds (German Shepherd, Labrador Retriever, Dachshund, Beagle, Doberman Pinscher, German Spitz and Pug) were collected from the ventral abdominal region. Using standard histological techniques, histology and the size and distribution of sweat glands were analysed. The results revealed significant variations in gland size and number among different breeds. Breeds like the German Spitz, German Shepherd and Dachshund had the largest sweat gland diameters, suggesting a better capacity for thermoregulation. In contrast, the Pug, Doberman Pinscher and Labrador Retriever had fewer and smaller glands. Dachshund stood out for possessing both the highest number and large-sized glands, while German Spitz had fewer but larger glands, compensating for the lesser number. The types of sweat glands predominating in ventral abdominal regions in dogs were apocrine glands. It was concluded that significant differences existed in the number and size of the sweat glands among different breeds which play a key role in thermoregulation. Keywords: Sweat glands, dogs, breed comparison
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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 | 0.002 | 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) | 0.001 | 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".