Bibliographic record
Abstract
Colorectal cancer is a rare disease in the pediatric age group and, when present, suggests an underlying genetic predisposition. The most common hereditary colon cancer susceptibility condition, Lynch syndrome (LS), previously known as hereditary nonpolyposis colorectal cancer, is an autosomal dominant condition caused by a germline mutation in 1 of 4 DNA mismatch repair (MMR) genes: MLH1, MSH2, MSH6, or PMS2. The mutation-prone phenotype of this disorder is associated with gastrointestinal, endometrial, and other cancers and is now being identified in both symptomatic adolescents with malignancy as well in asymptomatic mutation carriers who are at risk for a spectrum of gastrointestinal and other cancers later in life. We review the DNA MMR system, our present understanding of LS in the pediatric population, and discuss the newly identified biallelic form of the disease known as constitutional mismatch repair deficiency syndrome. Both family history and tumor characteristics can help to identify patients who should undergo genetic testing for these cancer predisposition syndromes. Patients who carry either single allele (LS) or double allele (constitutional mismatch repair deficiency syndrome) mutations in the MMR genes benefit from cancer surveillance programs that target both the digestive and extraintestinal cancer risk of these diseases. Because spontaneous mutation in any one of the MMR genes is extremely rare, genetic counseling and testing are suggested for all at-risk family members.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".