Bibliographic record
Abstract
BACKGROUND: Uterine sarcomas are rare malignancies that resemble benign uterine leiomyomata. Uterine artery embolization is offered increasingly for treatment of uterine leiomyomata, which might lead to embolization of undiagnosed uterine sarcoma. CASE: A 52-year-old woman, gravida 7, para 6, with perimenopausal menometrorrhagia was diagnosed with uterine leiomyomata after physical examination and transvaginal ultrasound. An endometrial biopsy was negative for malignancy. After medical treatment was unsuccessful, she had uterine artery embolization. She then passed a piece of tissue from her vagina, the pathology report of which was necrotic high-grade sarcoma. During surgery we confirmed that the tumor was confined to the uterus. CONCLUSION: Uterine sarcoma cannot be diagnosed except by pathologic examination of a resected specimen. Women considering uterine artery embolization for treatment of apparent leiomyomata should be counseled on the risk of decreased survival by delaying diagnosis and treatment of uterine sarcoma.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 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".