EXCICISION OF LIPOMA IN THE SINISTRA FEMORIS REGION SKIN IN A MIX LABRADOR AND POMERANIAN DOG
Bibliographic record
Abstract
Lipoma is a benign tumor consisting of mature adipocyte tissue that grows abnormally. This case study aims to determine about treatment and diagnosis of lipoma in dog. The animal in this case is a female mixed Labrador and Pomeranian dog, 11 years old, weighing 17.6 kg with complaints of a large mass that hang in the area of the hind limb. Supportive examination was carried out by histopathological examination. The presence of tumor cells in the form of spindle cells, homogeneous maturation of lipid cell poiferation were found. Based on its medical history, clinical examination, and laboratory examination, the dog was diagnosed with Lipoma. Premedication was given in the form of atropine sulfate at a dose of 0.02 mg/kg BW (SC), and anesthesia in the form of a combination of xylazine at a dose of 2 mg/kg of BW and ketamine at a dose of 13 mg/kg BW (IM). Surgery was performed with excision of the tumor mass in the hind leg area. Postoperatively, the antibiotic cefotaxime was given at a dose of 20 mg/kg of BW (IM), followed by administration of cefixime trihydrate syrup 100 mg/5ml at a dose of 10 mg/kg BW by PO for five days and anti-inflammatory tolfenamic acid at a dose of 4 mg/kg BW by SC for three days. Neomycin Sulfate powder was given sufficiently until the wound dries. On the 12th day of postoperative, the wound fused and there were no complications. In conclusion, based on the anamnesis and all supportive examinations, the dog was diagnosed with lipoma on hind legs, and was treated with tumor tissue excision. The dog’s condition was observed to be stable, and no other complaints were reported post-treatment.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".