Li-Fraumeni Syndrome and p53 in 2015: Celebrating their Silver Anniversary
Bibliographic record
Abstract
In a typical morning in the Cancer Genetics Clinic at The Hospital for Sick Children in Toronto, the following array of patients and families might be seen: a family of three children, all harbouring a mutation of the succinyl dehydrogenase C gene inherited from their father who had had extensive surgery several years ago for a secreting paraganglioma; three families with Li-Fraumeni syndrome, each with at least one child harbouring a TP53 gene mutation conferring a lifetime risk of cancer approaching 100% and currently undergoing surveillance for early tumour detection; two children with Li-Fraumeni syndrome undergoing treatment for cancer - one having had three cancer diagnoses before 19 months of age and the other just completing therapy for metastatic adrenocortical carcinoma at age 3; two children with von Hippel-Lindau disease being monitored for persistent pancreatic neuroendocrine tumors and cerebellar hemangioblastomas, respectively; and one child with Beckwith-Wiedeman syndrome and Wilms tumor and another child completing therapy for a pleuropulmonary blastoma (PPB).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".