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Using genetic diagnostics in hemophilia and von Willebrand disease

2015· review· en· W2202176702 on OpenAlex
Laura L. Swystun, Paula James

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHematology · 2015
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsVon Willebrand diseaseVon Willebrand factorDiseaseMolecular diagnosticsMedicineGenetic testingCoagulationPrenatal diagnosisImmunologyIntensive care medicineBioinformaticsGeneticsBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Most bleeding disorders encountered in clinical practice will be diagnosed, at least initially, by phenotypic assays. However, since the characterization of the genes that encode coagulation factors in the 1980s, significant progress has been made in translating this knowledge for diagnostic and therapeutic purposes. For hemophilia A and B, molecular genetic testing to determine carrier status, prenatal diagnosis, and likelihood of inhibitor development or anaphylaxis to infused coagulation factor concentrates is an established component of comprehensive clinical management. In contrast, although significant recent advances in our understanding of the molecular genetic basis of von Willebrand disease (VWD) have allowed for the development of rational approaches to genetic diagnostics, questions remain about this complex genetic disorder and how to incorporate emerging knowledge into diagnostic strategies. This article will review the state-of-the-art for molecular diagnostics for both hemophilia and VWD.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.962
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.369
Teacher spread0.295 · 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