Weight Gain After Oophorectomy Among Women with a <i>BRCA1</i> or <i>BRCA2</i> Mutation
Bibliographic record
Abstract
AIM: To measure weight gain among unaffected women with a BRCA1 or BRCA2 mutation after undergoing an oophorectomy. PATIENTS & METHODS: We compared the bodyweight of women with (n = 405) and without an oophorectomy (n = 741) at baseline as well as the rate of weight change prior to and following surgery among 1454 BRCA mutation carriers who had an oophorectomy. RESULTS: There was a small and non-significant difference in bodyweight between BRCA mutation carriers who had an oophorectomy compared with those women who did not (151.5 vs 149.1 pounds; p = 0.26). There was an increase in bodyweight with increasing age, but this relationship did not differ prior to and following surgery (p comparing the slope parameters = 0.78). CONCLUSION: Oophorectomy is not associated with significant weight gain in high-risk women.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".