Mammary Tumors in dogs: Age, Breed, Gender, Rearing, and Diet Factors
Bibliographic record
Abstract
Mammary neoplasms, are the second most common canine cancer type that pose a significant health concern for the dogs. This research explores the prevalence and identifies various risk factors associated with their occurrence. Among 45 confirmed cases, mammary tumors were most common in dogs aged 8 to 12 years. Female dogs were more susceptible, attributed to estrogen's effect on mammary glands. The highest occurrence of mammary tumors was identified in Labrador Retrievers and Crossbred dogs. The highest incidence of CMTs was noted in the inguinal mammary gland. Following this, the caudal abdominal gland, cranial thoracic mammary gland, while the caudal thoracic glands accounted the least number of cases. In the current study, there was higher incidence of neoplasms in underweight dogs and in owned dogs reared in outdoors. This study provides insights into the epidemiology of mammary tumors in dogs, with respect to age, gender, breed, environmental exposures, and dietary practices as significant.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".