Bibliographic record
Abstract
A twelve-year-old airport sniffer male Labrador dog was brought to Veterinary Clinical Complex, VCRI, Namakkal with the history of sudden seizures and drooling of saliva. However, the dog was found dead while on arrival at the Veterinary Clinical Complex. The dog carcass was referred to the Department of Veterinary Pathology, VCRI, Namakkal for necropsy. On gross examination, multiple blackish nodular growths in the oral cavity; leathery appearance of lungs with tiny raised greyish nodules; dark blackish raised nodules in spleen; shrunken kidneys with focal blackish areas in cortico-medullary junction; blackish discolouration with haemorrhage in intestine; thickened urinary bladder and prostate gland were observed. Cytological examination of oral growth revealed clusters of melanin-laden melanocytes with anisocytosis, anisokaryosis, prominent nucleoli and intracytoplasmic coarse granular melanin pigments. Histopathological examination of the oral growth exhibited replacement of normal stratified squamous epithelium with numerous melanin-laden melanocytes. In addition, melanin-laden melanocytes were also noticed in various organs like lungs, spleen, kidney and intestine. This case deals with oral melanoma with multicentric metastasis to various organs in a sniffer dog.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".