How much do we really know about von Willebrand disease?
Bibliographic record
Abstract
PURPOSE OF REVIEW: In the last nine decades, large advances have been made toward the characterization of the pathogenic basis and clinical management of von Willebrand disease (VWD), the most prevalent inherited bleeding disorder. Pathological variations at the von Willebrand factor (VWF) locus present as a range of both quantitative and qualitative abnormalities that make up the complex clinical spectrum of VWD. This review describes the current understanding of the pathobiological basis of VWD. RECENT FINDINGS: The molecular basis of type 2 (qualitative abnormalities) and type 3 VWD (total quantitative deficiency) have been well characterized in recent decades. However, knowledge of type 1 VWD (partial quantitative deficiency) remains incomplete because of the allelic and locus heterogeneity of this trait, and is complicated by genetic variability at the VWF gene, interactions between the VWF gene and the environment, and the involvement of external modifying loci. Recent genome wide association studies and linkage analyses have sought to identify additional genes that modify the type 1 VWD phenotype. SUMMARY: Understanding the pathogenic basis of VWD will facilitate the development of novel treatment regimens for this disorder, and improve the ability to provide complementary molecular diagnostics for type 1 VWD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".