GoldVariants, a resource for sharing rare genetic variants detected in bleeding, thrombotic, and platelet disorders: Communication from the ISTH SSC Subcommittee on Genomics in Thrombosis and Hemostasis
Bibliographic record
Abstract
The implementation of high-throughput sequencing (HTS) technologies in research and diagnostic laboratories has linked many new genes to rare bleeding, thrombotic, and platelet disorders (BTPD), and revealed multiple genetic variants linked to those disorders, many of them being of uncertain pathogenicity when considering the accepted evidence (variant consequence, frequency in control datasets, number of reported patients, prediction models, and functional assays). The sequencing effort has also resulted in resources for gathering disease-causing variants associated with specific genes, but for BTPD, such well-curated databases exist only for a few genes. On the other hand, submissions by individuals or diagnostic laboratories to the variant database ClinVar are hampered by the lack of a submission process tailored to capture the specific features of hemostatic diseases. As we move toward the implementation of HTS in the diagnosis of BTPD, the Scientific and Standardization Committee for Genetics in Thrombosis and Haemostasis has developed and tested a REDCap-based interface, aimed at the community, to submit curated genetic variants for diagnostic-grade BTPD genes. Here, we describe the use of the interface and the initial submission of 821 variants from 30 different centers covering 14 countries. This open-access variant resource will be shared with the community to improve variant classification and regular bulk data transfer to ClinVar.
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 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 | 0.009 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.060 | 0.027 |
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".