Bibliographic record
Abstract
PURPOSE OF REVIEW: Granulosa cell tumours of the ovary are an uncommon ovarian sex-cord stromal tumour. These neoplasms provide a spectrum of clinical presentations that span from the first to the tenth decade. Surgery represents the primary therapy for early stage disease; however, management of women with advanced disease is less clear. Because of their relative rarity, evidence to support decision-making in the management of granulosa cell tumours is limited. The purpose of this review is to provide the clinician with an updated knowledge of the clinical and molecular aspects of granulosa cell tumours in order to guide therapy. RECENT FINDINGS: The clinical stage, mitotic index and cellular atypia correlate most strongly with prognosis. However, these tumours may demonstrate heterogeneous genetic aberrations that can predict behaviour and response to therapy. Case series and reports suggest that postoperative combination chemotherapy is of most benefit in advanced disease. Serial measurements of serum inhibin may be helpful in the follow-up of these women, particularly in the post-menopausal group. SUMMARY: The pathology and treatment of women with granulosa cell tumours of the ovary is complex. Such women should be managed in a multidisciplinary gynaecological oncology unit. A better understanding of the molecular pathology may assist treatment.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".