A Clinical Review of Generalized Overgrowth Syndromes in the Era of Massively Parallel Sequencing
Bibliographic record
Abstract
The overgrowth syndromes are important to diagnose, not just for accurate genetic counseling, but also for knowledge surrounding cancer surveillance and prognosis. There has been a recent expansion in the number of genes associated with a mendelian overgrowth phenotype, so this review updates previous classifications of overgrowth syndromes. We also describe a clinical and molecular approach to the investigation of individuals presenting with overgrowth. This review aims to assist the clinical diagnosis of generalized overgrowth syndromes by outlining the salient features of well-known overgrowth syndromes alongside the many syndromes that have been discovered and classified more recently. We provide key clinical "handles" to aid clinical diagnosis and a list of genes to aid with panel design when using next generation sequencing, which we believe is frequently needed due to the overlapping phenotypic features seen between overgrowth syndromes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".