INCIDENCE OF CANINIE NEOPLASMS IN AND AROUND HYDERABAD, ANDHRA PRADESH
Bibliographic record
Abstract
A total of 68 samples were collected, out of which 31 (45.59%) were benign and 37 (54.41%) were malignant tumours. Tumours were classified into epithelial 40(58.83%), mesenchymal 20 (29.40%), round cell 5 (7.36%) and mixed tumours 3 (4.41%). The highest risk of development of various tumours was found in the age group of 7-9 years, followed by 4-6 years, above 9 years and below 3 years and the incidence was 29 (42.65%), 20(29.41%),19 (27.94%) and 1 (1.47% ) respectively. The frequency of occurrence of neoplasms was slightly higher in females 38(55.88%) compared to the males 30 (44.12%). Among the breeds affected Pomeranian breed represented more with 18 (26.50%) followed by non descriptive 16 (23.52%), German Shepherd 16 (23.52%), Labrador 6 (8.82%), Doberman 6 (1.47%), Dachshund and Rottweiler 2 (2.94%), each one of Collie and Great Dane (1.47%). The organ wise incidence of tumours included skin and mesenchymal tumours 29 (42.65%), mammary tumours 17 (25%), joint and bone tumours 9 (13.23%), vaginal tumours 5 (7.53%), testicular tumours 4 (5.88%), vulva and penis 3 (4.41%), ovarian tumours 2 (2.94%) and each one of transitional cell carcinoma and prostate carcinoma (1.47%).
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".