BRCA1 founder mutations compared to ovarian cancer in Belarus
Bibliographic record
Abstract
In Belarus and other Slavic countries, founder mutations in the BRCA1 gene are responsible for a significant proportion of breast cancer cases, but the data on contribution of these mutations to ovarian cancers are limited. To estimate the proportion of ovarian cancers in Belarus, which are dependent on BRCA1 Slavic founder mutations, we sought the presence of three most frequent mutations (BRCA1: 5382insC, C61G and, 4153delA) in 158 consecutive unselected cases of ovarian cancer. One of the three founder mutations was present in 25 of 158 unselected cases of ovarian cancer (15.8 %). We recommend that all cases of ovarian cancer in Belarus be offered genetic testing for these founder mutations. Furthermore, genetic testing of the Belarusian population will provide the opportunity to prevent a significant proportion of ovarian cancer.
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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 | 0.000 |
| 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".