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Record W2407695468

BK virus associated nephropathy in renal transplantation: where do we stand.

2011· article· en· W2407695468 on OpenAlexaff
Ankur Gupta, Prem Gupta

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineBK virusImmunosuppressionContext (archaeology)NephropathyVirusIntensive care medicineEpidemiologyImmunologyClinical trialTransplantationKidney transplantationVirologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

BK virus is an increasingly identified complication in renal allograft recipients. During the last decade, the use of potent immunosuppressive medications has led to reemergence of this virus. Despite the paucity of randomized trials, we have come a long way in the knowledge of BK virus associated nephropathy. This review highlights the epidemiological, pathogenic, pathological, and clinical aspects of BK virus. It summarizes advances made in prophylaxis and treatment strategies to curtail this virus in an era of modern immunosuppression. The old word of wisdom- prevention is better than cure- might be relevant in context of BK virus prophylaxis with flouroquinolones in years to follow.

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)0.010
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.002
Science and technology studies0.0020.005
Scholarly communication0.0050.020
Open science0.0020.003
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0050.003

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 head0.030
GPT teacher head0.226
Teacher spread0.197 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2011
Admission routes1
Has abstractyes

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