Benign Smooth Muscle Tumors (Leiomyomas) of Deep Somatic Soft Tissue
Bibliographic record
Abstract
Leiomyomas of deep soft tissue are extremely rare and should only be diagnosed following adherence to stringent histological criteria, namely, the absence of nuclear atypia and of coagulative tumor necrosis. Whether extremely low counts of, or even any, mitotic activity are acceptable when making a diagnosis of leiomyoma in deep soft tissue sites is controversial. The morphology and immunophenotype of smooth muscle tumors in deep soft tissue are similar to their counterparts irrespective of topography. It is interesting to note that leiomyomas of deep soft tissue (extremity and retroperitoneum) are often hyalinized/sclerosed and calcified. However, the prediction of their behavior and correct codification is dependent on thorough, meticulous search for mitoses and necrosis. Leiomyomas of deep soft tissue in the extremity should be devoid of mitoses and "significant" cytological atypia. An occasional larger, slightly pleomorphic cell in the midst of bland spindle cells, can be regarded as insignificant atypia. If any mitotic activity and several atypical cells are encountered in smooth muscle tumors of deep soft tissue of the extremity, it would be prudent to invoke the appellation of smooth muscle tumor of uncertain malignant potential and advocate wide local excision and follow-up.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".