Collaborative multidisciplinary team approach to fertility issues among adolescent and young adult cancer patients
Bibliographic record
Abstract
Cancer treatment and the field of reproductive technology have each made impressive advancements in the last decade. Improved cancer treatment and survival rates have increased the number of cancer survivors, who might benefit from an array of fertility preservation strategies provided by emerging and advanced assisted conception technology. The challenge becomes bridging the gap between these two separate disciplines to ultimately improve the quality of life for cancer survivors. This paper discusses the issues and process involved with bringing these two teams of health-care professionals together. This model provides a framework for coordinating efforts in providing fertility preservation options to patients undergoing treatment for cancer. Effective multidisciplinary teams that include: oncologists, nurses in the specialties of oncology and infertility, social workers, reproductive endocrinology and infertility specialists, andrologists, and embryologists are required to work together in order to achieve success. The result of this unique team approach is not only a cancer survivor, but one whose quality of life might be enhanced by being able to have a child of his or her own in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".