Metastatic malignant melanoma in dog-A case report
Bibliographic record
Abstract
A three year old male Labrador dog was presented with history of anorexia, dyspepsia, respiratory distress and weakness. On physical examination, the dog showed small round lumps on the skin. Ultrasonography examination of heart, lung, liver and kidney depicted multifocal abnormal tissue. Multifocal neoplastic growths in different organs were tentatively diagnosed and the dog was symptomatically treated until death. On postmortem examination, multiple dark black masses varying from 0.5 to 3 cm in diameter were detected in heart, lung, liver, kidney, bladder and intestine. Histopathologically, these masses were diagnosed as malignant melanoma and variable melanin pigments within the neoplastic cells were confirmed by Fontana-silver method of staining technique. These tumors were considered to have originated from the primary site of skin or intestine.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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".