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Record W2756016513 · doi:10.1182/blood-2017-05-786699

Novel insights into the clinical phenotype and pathophysiology underlying low VWF levels

2017· article· en· W2756016513 on OpenAlexaff
Michelle Lavin, Sonia Águila, Sonja Schneppenheim, Niall Dalton, Kenneth L. Jones, Jamie M. O’Sullivan, Niamh O’Connell, Kevin M. Ryan, Barry White, Mary Byrne, Marie Rafferty, Mairead M. Doyle, Margaret Nolan, Roger J. S. Preston, Ulrich Budde, Paula James, Jorge Di Paola, James S. O’Donnell

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood Institute
KeywordsPathophysiologyPhenotypeMedicineBiologyImmunologyGeneticsInternal medicine

Abstract

fetched live from OpenAlex

< .05). In response to 1-desamino-8-D-arginine vasopressin (DDAVP), peak VWF:Ag levels exceeded 100 IU/dL in 88% of patients and was sustained >100 IU/dL after 4 hours in 72% of subjects. In conclusion, our novel data suggest that low VWF levels can be associated with significant bleeding and are predominantly due to reductions in VWF synthesis and/or constitutive secretion. Although enhanced VWF clearance may contribute to the pathophysiology in some individuals, the absolute reduction in VWF plasma half-life is usually mild and not sufficient to significantly impact upon the duration of DDAVP-induced VWF response. This trial was registered at www.clinicaltrials.gov as #NCT03167320.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.085
GPT teacher head0.358
Teacher spread0.273 · 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

Citations134
Published2017
Admission routes1
Has abstractyes

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