Hemipelvectomy and Wound Revision Surgery on a 10-Year-Old Golden Retriever
Bibliographic record
Abstract
A 10-year-old female spayed Golden Retriever was transferred to Cornell University Hospital for Animal?s Soft Tissue Surgery service for removal of a large abdominal mass. She originally presented to her referring veterinarian for persistent constipation and ribbon-like feces, and radiographs showed a large abdominal mass. At intake, an occluding mass was identified on rectal palpation. Ultrasound and computed tomography exams revealed a proliferative bone lesion originating from the left ilium. A hemipelvectomy and limb amputation were performed to remove the mass. During the surgery, a loosened anal purse-string suture resulted in surgical site contamination. The area was lavaged profusely and closed in a normal fashion. Histopathology identified the mass as a Grade I multilobular osteochondrosarcoma, a rare neoplasia of the flat bones that is most often found on the skull. The patient presented four days later for surgical site dehiscence, and a wound revision surgery was performed to culture and debride the necrotic tissue. Culture revealed multi-drug resistant Enterococcus faecium infection. The patient was switched to oral chloramphenicol and was discharged after four days in the intensive care unit. On recheck 12 days later the patient was ambulating well, and the incision margins were healthy and healing.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".