Clinical implications of the breast cancer susceptibility genes<i>BRCA1</i>and<i>BRCA2</i>
Bibliographic record
Abstract
Genetic testing for BRCA1 and BRCA2 mutations has become an important part of the practice of medical oncology and clinical genetics over the past decade. Increasing numbers of women are requesting a genetic test so that they may better understand their personal risks of breast and ovarian cancer, and so that they may take appropriate measures to reduce the risk. Several of the risk factors can be modified, including breastfeeding and the use of oral contraceptives. A significant number of women opt for preventive mastectomy or oophorectomy, which will dramatically reduce the risks of breast and ovarian cancer. Chemoprevention with tamoxifen is still uncommon, largely due to women's fears of the side effects of the drug. A number of studies have shown that magnetic resonance imaging is superior to conventional mammography in terms of the early detection of breast cancer in the high-risk population. This article explores what is known about assessing genetic risk and the evidence supporting a range of preventive strategies.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".