Correction: Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the Prospective Lynch Syndrome Database
Bibliographic record
Abstract
Correction to: Genetics in Medicine22:2020; https://doi.org/10.1038/s41436-019-0596-9, published online 24 July 2019. The original version of this Article did not contain details of Dutch Cancer Society (DCS) funding (grant number UL 2017-8223) in the Acknowledgements section. This has now been corrected in both the PDF and HTML versions of the Article. These authors contributed equally: Julian R. Sampson, Mev Dominguez-Valentin, Toni T Seppälä. The original article can be found online at https://doi.org/10.1038/s41436-019-0596-9. Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the Prospective Lynch Syndrome DatabaseGenetics in MedicineVol. 22Issue 1PreviewPathogenic variants affecting MLH1, MSH2, MSH6, and PMS2 cause Lynch syndrome and result in different but imprecisely known cancer risks. This study aimed to provide age and organ-specific cancer risks according to gene and gender and to determine survival after cancer. Full-Text PDF Open Access
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".