Applicazioni tecnico metodologiche per il miglioramento della performance riproduttiva nel cane di allevamento
Bibliographic record
Abstract
Breeders often complain about a decreased fertility and veterinarians are more and more requested to solve fertility problems.<br/> \nIn this study 5 breeds of dogs were selected on the basis of an infertility anamnesis. Newfoundland, English Bulldog, Hold English Mastiff, Great Dane and Dogue de Bordeaux. The purpose of this research was to determine the correlation between various fertility parameters and try to improve the production. There was no relation between parity and breeds in our population. In this study, there were more natural covers in great danes as compared to other breeds. English bulldogs and Old English Mastiffs in particular had significantly less natural breeding. There were significantly more positive pregnancy diagnoses in both primiparous and multiparous bitches in all breeds but in the great danes. This suggests a reduced fertility in that breed. Considering the number of puppies produced by a particular tecnic of insemination there is an effect only in Great Dane. In that breed, it seems that natual breeding is more efficient than the Artificial Insemination. A significant effect of the breed on the type of delivery was demonstrated (more c-sections in Bulldogs and Mastiffs, more natural deliveries in Newfoundland and Dogues de Bordeaux and no difference in Great Danes). Primiparous were not less likely to give birth naturally than multiparous bitches. \nPerpetuating artificial reproduction in dogs that, under natural conditions, could never contribute to the genetic pool, the low fertility in some bloodlines is probably explained by wrong breeder selection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".