Risk factors for ovarian cancer and early-onset breast cancer in Mongolia.
Bibliographic record
Abstract
OBJECTIVE: To determine if there are founder BRCA1 mutations in the Mongolian population. METHODS: Seventeen women with ovarian cancer, 14 women with premenopausal breast cancer and one woman with both cancer types were interviewed to obtain family history, and hormonal, reproductive and environment risk factor information. Blood was collected for DNA analysis from these women to determine the frequency of BRCA1 and BRCA2 mutations in Mongolia. RESULTS: Two patients had two first-degree relatives with cancer and nine women had one first degree relative with cancer. Two women had the unique BRCA1 mutation previously described. These two women were not related but their parents were from the same tribe and they lived in the same imak (province). Only one other patient was of this tribal background and from the same region; however, she did not have the BRCA1 mutation. CONCLUSION: A substantial proportion of Mongolian woman with ovarian cancer or early-onset breast cancer may be due to a founder BRCA1 mutation 3452delA.
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 | 0.000 |
| 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) | 0.002 | 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 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".