Myopericytoma on the nasal turbinate
Bibliographic record
Abstract
Abstract Myopericytoma is a mesenchymal tumour that shares characteristics with other soft tissue tumours including glomus tumours and myofibromas. These pericytic tumours show characteristic perivascular growth patterns (Sbaraglia M, Bellan E, Dei Tos AP. The 2020 WHO classification of soft tissue tumours: news and perspectives. Pathologica 2021;113:70–84. https://doi.org/10.32074/1591-951X-213). Myopericytoma differentiates itself as it tends to have a spindle shape histologically, rather than an epithelioid shape as with the glomus variety. Myopericytoma rarely demonstrate malignant behaviour. A 67-year-old male presented to our clinic with complaints of increased frequency of right sided epistaxis for several months. The epistaxis episodes were controlled with oxymetazoline spray and manual pressure to the nasal tip. Office nasal endoscopy revealed a mass emanating from the anterior end of the right inferior turbinate. Complete excision was performed endoscopically. Histopathological analysis revealed myopericytoma, a rare tumour typically arising from the epithelium or submucosa. This case underscores the need for otolaryngologists to consider perivascular tumours in the differential diagnosis of intranasal masses as complete excision is recommended to avoid recurrence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".