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Record W4404852820 · doi:10.36660/abc.20230858i

Predictive Value of Cardiac Biomarkers on Delayed Graft Function in Renal Transplant Patients

2024· article· pt· W4404852820 on OpenAlexaff
Rodrigo Pinheiro Amantéa, Virgílio da Rocha Olsen, Laura Caroline Tavares Hastenteufel, Flávia K. Borges, Roberto Ceratti Manfro, Lívia Adams Goldraich, Nadine Clausell

Bibliographic record

VenueArquivos Brasileiros de Cardiologia · 2024
Typearticle
Languagept
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineRenal transplantPredictive valueRenal functionCardiologyInternal medicineValue (mathematics)Cardiac function curveTransplantationHeart failure

Abstract

fetched live from OpenAlex

Introduction Cardiovascular (CV) disease is the leading cause of death among adult kidney transplant recipients, accounting for 25% of deaths in patients with functioning grafts. Cardiac biomarkers, in particular, brain natriuretic peptide (BNP) and cardiac troponin (cTn), are the most studied biomarkers for predicting the risk of major adverse cardiovascular events (MACE) in end-stage kidney disease and kidney transplant., Myocardial injury after non-cardiac surgery (MINS) is a new clinical entity with relevant clinical and prognostic implications. It is defined as [...]

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.270
Teacher spread0.255 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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