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von <scp>W</scp>illebrand's disease: a report from a meeting in the <scp>Å</scp>land islands

2012· article· en· W2049169130 on OpenAlexaff
Erik Berntorp, I. R. Peake, Ulrich Budde, Michael Laffan, Robert R. Montgomery, Jerzy Windyga, Anne Goodeve, Pia Petrini, Mario von Depka, Wolfgang Miesbach, David Lillicrap, Augusto B. Federici, Riitta Lassila, G C White

Bibliographic record

VenueHaemophilia · 2012
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood InstituteBritish Heart Foundation
KeywordsMedicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

von Willebrand's disease (VWD) is probably the most common bleeding disorder, with some studies indicating that up to 1% of the population may have the condition. Over recent years interest in VWD has fallen compared to that of haemophilia, partly the result of focus on blood-borne diseases such as HIV and hepatitis. Now the time has come to revisit VWD, and in view of this some 60 international physicians with clinical and scientific interest in VWD met over 4 days in 2010 in the Åland islands to discuss state-of-the-art issues in the disease. The Åland islands are where Erik von Willebrand had first observed a bleeding disorder in a number of members of a family from Föglö, and 2010 was also the 140th anniversary of his birth. This report summarizes the main papers presented at the symposium; topics ranged from genetics and biochemistry through to classification of VWD, pharmacokinetics and laboratory assays used in the diagnosis of the disease, inhibitors, treatment guidelines in different age groups including the elderly who often have comorbid conditions that present challenges, and prophylaxis. Other topics included managing surgeries in patients with VWD and the role of FVIII in VWF replacement, a controversial subject.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations30
Published2012
Admission routes1
Has abstractyes

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