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Record W4381393044 · doi:10.1016/j.hpb.2023.05.090

Factor V as a predictor of graft loss after liver transplant

2023· article· en· W4381393044 on OpenAlexaff
Annabel Gravely, Marco P. A. W. Claasen, Tommy Ivanics, Erin Winter, Markus Selzner, Gonzalo Sapisochín

Bibliographic record

VenueHPB · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineLiver transplantationLiver dysfunctionInternal medicinePredictive valueRetrospective cohort studyGraft rejectionGastroenterologyLiver function testsLiver functionSurgeryTransplantation

Abstract

fetched live from OpenAlex

Background: In search for an early and accurate assessment of graft dysfunction, a retrospective study found that low post-operative day (POD) 1 measurements of plasma Factor V in liver transplant recipients were associated with both Early Allograft Dysfunction and graft loss when stratified by a cut-off of 0.36 U/mL. Our study aimed to prospectively validate these findings and to build on the current knowledge regarding the value of Factor V as a marker for post-transplant liver function.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.999

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)0.0010.000

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 head0.016
GPT teacher head0.272
Teacher spread0.256 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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