Consensus views arising from the 60th Study Group: Gynaecological Cancers: Biology and therapeutics
Bibliographic record
Abstract
This chapter discusses the biology of and therapeutics for gynaecological cancers such as vulval cancer, cervical cancer and ovarian cancer. The most common type of ovarian cancer, high-grade serous cancer, is characterised by mutation of the p53 (TP53) gene. All women with newly diagnosed high-grade serous ovarian carcinoma should have an accurate family history taken, and be referred for genetic assessment and considered for BRCA1 and BRCA2 mutation testing if appropriate. Within clinical trials, central pathological review is needed when treatment depends on morphological sub-type or other pathological parameters. Functional imaging in multicentre trials should be implemented with strict quality control to ensure standardisation and reproducibility. Evaluation of novel surgical strategies, such as robotics, should occur through well-conducted clinical trials. In surgery for ovarian cancer, whether carried out as a primary or a delayed procedure, the aim should be to remove all visible disease.
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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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.020 | 0.014 |
| Insufficient payload (model declined to judge) | 0.042 | 0.022 |
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".