INFLUENCE OF BREED, AGE, SIZE AND PARITY OF THE DAM ON THE FREQUENCY DISTRIBUTION OF DYSTOCIAS IN CANINES
Bibliographic record
Abstract
The influence of breed, age, size and parity of the bitch on the incidence of dystocia was analyzed. Nearly 30 per cent of dystocia cases presented (n=1236) were either in Labrador Retriever or German Shepards.However, 23.63 per cent of all dystocia encountered were in brachycephalic breeds like Pug, Bull dog and Boxers. The size of the breed was found to have a significant effect on the incidence of dystocia, the incidence being significantly higher in medium and large size breed. It was also observed that the incidence of the dystocia was highest in bitches aged 2-4 years and gradually declined with the advancing age. Bitches less than 4 years accounted for nearly 62 per cent of the dystocia cases suggesting the preference of owners to breed animals at their younger age and withhold breeding in aged animals. In the present study 31.07 per cent of cases referred were primiparous and the rest had delivered 1-8 times. The incidence of dystocia decreased progressively with increase in parity and the least incidence was recorded in animals with more than 5 previous deliveries.
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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 | 0.000 |
| 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".