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Record W2052918149 · doi:10.1111/bjh.12249

The molecular characterization of von <scp>W</scp>illebrand disease: good in parts

2013· review· en· W2052918149 on OpenAlexafffund
Paula D. James, David Lillicrap

Bibliographic record

VenueBritish Journal of Haematology · 2013
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of HealthCanadian Hemophilia SocietyHeart and Stroke Foundation of Canada
KeywordsVon Willebrand diseaseVon Willebrand factorDiseaseMolecular pathologyMolecular geneticsBiologyLocus (genetics)GeneticsImmunologyGeneMedicinePathologyPlatelet

Abstract

fetched live from OpenAlex

Since the cloning of the gene that encodes von Willebrand factor (VWF), 27 years ago, significant progress has been made in our understanding of the molecular basis of the most common inherited bleeding disorder, von Willebrand disease (VWD). The molecular pathology of this condition represents a range of genetic mechanisms, some of which are now very well characterized, and others that are still under investigation. In general, our knowledge of the molecular basis of type 2 and 3 VWD is now well advanced, and in some instances this information is being used to enhance clinical management. In contrast, our understanding of the molecular pathogenesis of the most common form of VWD, type 1 disease, is still at an early stage, with preliminary evidence that this phenotype involves a complex interplay between environmental factors and the influence of genetic variability both within and outside of the VWF locus.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.015
GPT teacher head0.280
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations35
Published2013
Admission routes2
Has abstractyes

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