A genome wide linkage search for breast cancer susceptibility genes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mutations in known breast cancer susceptibility genes account for a minority of the familial aggregation of the disease. To search for further breast cancer susceptibility genes, we performed a combined analysis of four genome-wide linkage screens, which included a total of 149 multiple case breast cancer families. All families included at least three cases of breast cancer diagnosed below age 60 years, at least one of whom had been tested and found not to carry a BRCA1 or BRCA2 mutation. Evidence for linkage was assessed using parametric linkage analysis, assuming both a dominant and a recessive mode of inheritance, and using nonparametric methods. The highest LOD score obtained in any analysis of the combined data was 1.80 under the dominant model, in a region on chromosome 4 close to marker D4S392. Three further LOD scores over 1 were identified in the parametric analyses and two in the nonparametric analyses. A maximum LOD score of 2.40 was found on chromosome arm 2p in families with four or more cases of breast cancer diagnosed below age 50 years. The number of linkage peaks did not differ from the number expected by chance. These results suggest regions that may harbor novel breast cancer susceptibility genes. They also indicate that no single gene is likely to account for a large fraction of the familial aggregation of breast cancer that is not due to mutations in BRCA1 or BRCA2.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it