Recommendations for Follow-up Care for Gynecologic Cancer Survivors
Bibliographic record
Abstract
Gynecologic cancer survivors are expected to increase in number over the coming years. This is attributable in part to an increased incidence of gynecologic malignancies as the population ages. Earlier detection and improved treatments will lead to improved survival. Women who have completed their cancer treatment and are disease-free enter a phase of follow-up care. This care can be provided by gynecologic oncologists, general gynecologists, or primary care practitioners, depending on local practices and geographic area. The key components of follow-up include complete history and physical examination. There should be judicious use of appropriate testing to detect disease recurrence, assessment, and management of therapy-related symptoms and provision of psychosocial support. Well-woman care and ongoing screening for other malignancies remain an important component of care that should not be overlooked. This review provides recommendations regarding follow-up care for women with gynecologic malignancies. There is very little high-quality evidence available to guide such care.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".