Multi-Platform Curation in the Development of ACMG/AMP Specifications for Von Hippel Lindau (VHL) Disease
Bibliographic record
Abstract
Introduction: gene, including phenotype-driven and evidence-based criteria, somatic and germline mutational hotspots, functional and in-silico data. Materials and Methods: Using the American College of Medical Genetics and Genomics (ACMG) guidance and the ClinGen Sequence Variant Interpretation (SVI) recommendations, the VCEP made substantial modifications to eight evidence codes (PVS1, PS3, PS4, PM1, BS2, BS3, BS4, BP5), while 14 had minor or no changes and 6 were not used (PM3, PP2, BP1, PP4, PP5/BP6). The VHL VCEP applied two literature sets of over >428 papers in Clinical Interpretations of Variants in Cancer (CIViC) and >8700 structured annotations using Hypothesis. Results: From 31 pilot variants, 15 remained pathogenic/likely pathogenic, 9 resolved to benign through the stand-alone benign evidence code and 7 variants with initial uncertain classifications, with many lacking additional literature, remained uncertain. Conclusion: The versioned VHL VCEP specifications are publicly available in the ClinGen Criteria Specifications Registry and will enhance the transparency and consistency of variant classifications for this highly sequenced hereditary cancer gene.
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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 | 0.025 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".