Zygomatic salivary mucocoele as a postoperative complication following caudal hemimaxillectomy in a dog
Bibliographic record
Abstract
Zygomatic mucocoele is reported as a postoperative complication occurring secondary to a caudal hemimaxillectomy in a two-year-old Labrador retriever. The dog was presented with a history of a rapidly growing oral mass, identified as a soft tissue sarcoma. A caudal hemimaxillectomy via an intraoral approach was performed as treatment for local control of the oral mass. Fifteen days postoperatively, periorbital swelling and exophthalmos developed on the ipsilateral side. The degree of swelling progressed and was identified by computed tomography, ultrasound and cytology as a salivary mucocoele. Zygomatic sialoadenectomy was performed via a modified lateral approach with zygomatic osteotomy. A small amount of discharge persisted from the surgical site but gradually resolved. Recurrence of the periorbital swelling and exophthalmos was noted 25 days later and further surgery was performed to excise residual salivary tissue. Adjuvant radiotherapy was performed, however local recurrence of the oral mass was identified 5 months postoperatively and the patient subsequently euthanased. Salivary mucocoele has been cited as a possible postoperative complication following maxillectomy and mandibulectomy procedures; however to the authors' knowledge, only one previous case report exists in the literature. The current case documents a zygomatic salivary mucocoele occurring subsequent to caudal hemimaxillectomy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".