Clinical management of mammary carcinoma in dogs: Current scenario
Bibliographic record
Abstract
Mammary carcinoma is one of the most common skin tumors of mammary gland area in canine. Fifty cases of mammary carcinoma were reported during the period of study at Teaching Veterinary Clinical Complex and Department of Veterinary Surgery and Radiology. Eighty animals were screened for selecting fifty mammary carcinoma and these are the subjects of present study population. The prevalence of tumors across the age groups were highest among 8 to 12 years, followed by 12 years and least in dogs below 8 years. Breed wise predisposition was highest among Labrador (36.67%), followed by Spitz and German shepherd (20% each), Mongrel (10%), Dachshund (6.67%), Rottweiler and beagle (3.33% each). More cases of mammary carcinoma were malignant (70%) with metastasis to regional lymph node a common finding. Malignancy criteria were size, hardness, of the tumor and metastasis to regional lymphocenter. Axillary lymph node for 1st, 2nd mammary gland tumor and inguinal, medial iliac lymph node for 2nd, 3rd, and 4th mammary gland were common site of regional metastasis. Most of the patient had clinical stage III tumor (30%) followed by stage II (23.33%). Three cases of stage IV mammary carcinoma were recorded in which three view thoracic radiography showed nodular opacities of the thorax and confirmed as positive sign of metastasis. Histopathologically, solid mammary carcinoma, fibroadenoma, adenocarcinoma were common types of carcinomas. Malignant mammary tumor dogs had significantly (p
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".