Salient features of sticker tumour in dogs and its diagnosis by cytopathology and histopathology technique
Bibliographic record
Abstract
Six dogs of various ages, breeds and sex showed tumourous growth confined to extragenital regions. The study was aimed at diagnosing tumourous growth using routine technique clinically and pathologically. Cytological techniques and later the results were compared with routine histopathology. Two male Labrador dogs, 1 female Spitz and 3 male non-descript dogs with tumour masses over and around the genital organ were used. Tumour impression sample and excised tumour were used as material for the study. Fine needle aspiration cytopathology (FNAC) with various cytological stains and routine histopathology with haematoxylin and eosin staining were performed. Grossly, the tumour masses appeared as single or multiple irregular, cauliflower like and had a tendency to bleed and in almost all cases colour was pink to red. Cytologically, the tumour yielded a homogenous, sheet-like high cellular mass. Cytoplasm with punctate vacuoles, anisokaryosis with anisonucleoliosis and coarse to reticulate nuclear chromatin were prominent features. Histopathology showed sheets of round cells with nuclear and cytoplasmic variations. The study concluded that cytopathology could be used as a quick, rapid, field diagnostic technique in combination with histopathology for the diagnosis of TVTs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".