Bibliographic record
Abstract
Prophylactic bilateral mastectomy, or preventive removal of the breasts, is an option for women who are at increased risk of developing breast cancer. Among the highest risk groups are those women with a significant family history of breast cancer and those with a known genetic predisposition to the disease. There are many issues surrounding prophylactic mastectomy. Recent research has demonstrated that prophylactic mastectomy may be effective in preventing breast cancer in high-risk women, as well as those with a known BRCA1/2 mutation. The limited research that has been done on the psychosocial implications of the preventive surgery suggests that prophylactic mastectomy may be effective in reducing distress levels in high-risk women and that most women who have had the surgery do not experience psychosocial difficulties. Overall, women who have had prophylactic mastectomy are satisfied with their decision to have the preventive surgery. However, women who choose prophylactic mastectomy may differ compared with those who do not. The results may not be generalizable to all high-risk women. Counseling of high-risk women, specifically those with a BRCA1 or BRCA2 mutation, should include a discussion of prophylactic mastectomy, including the medical and psychosocial risks and benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".