Dog sperm head morphometry: its diversity and evolution
Why this work is in the frame
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Bibliographic record
Abstract
Dogs have been under strong artificial selection as a consequence of their relationship with man. Differences between breeds are evident that could be reflected in seminal characteristics. The present study was to evaluate differences in sperm head morphometry between seven well-defined breeds of dog: the British Bulldog, Chihuahua, German Shepherd, Labrador Retriever, Spanish Mastiff, Staffordshire Terrier, and Valencian Rat Hunting dog. Semen samples were obtained by masturbation and smears stained with Diff-Quik. Morphometric analysis (CASA-Morph) produced four size and four shape parameters. Length, Ellipticity, and Elongation showed higher differences between breeds. MANOVA revealed differences among all breeds. Considering the whole dataset, principal component analysis (PCA) showed that PC1 was related to head shape and PC2 to size. Procluster analysis showed the British Bulldog to be the most isolated breed, followed by the German Shepherd. The PCA breed by breed showed the Chihuahua, Labrador Retriever, Spanish Mastiff, and Staffordshire Terrier to have PC1 related to shape and PC2 to size, whereas the British Bulldog, Valencia Rat Hunting dog, and German Shepherd had PC1 related to size and PC2 to shape. The dendrogram for cluster groupings and the distance between them showed the British Bulldog to be separated from the rest of the breeds. Future work on dog semen must take into account the large differences in the breeds' sperm characteristics. The results provide a base for future work on phylogenetic and evolutionary studies of dogs, based on their seminal characteristics.
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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 | 0.000 |
| 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) | 0.000 | 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 it