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Record W4307834505 · doi:10.1016/j.xkme.2022.100565

Steroids for IgA Nephropathy: A #NephJC Editorial on the TESTING trial

2022· editorial· en· W4307834505 on OpenAlexafffund
Anand Chellappan, Rachael Kermond, Tiffany Caza, Jade Teakell, Swapnil Hiremath

Bibliographic record

VenueKidney Medicine · 2022
Typeeditorial
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsUniversity of Ottawa
FundersDepartment of Medicine, University of Toronto
KeywordsMedicineNephropathyAzathioprineInternal medicineImmunosuppressionPopulationKidney diseaseDiseaseEndocrinologyDiabetes mellitus

Abstract

fetched live from OpenAlex

IgA nephropathy (IgAN) is one of the most common glomerular diseases worldwide and carries a high disease burden with 30%-40% of patients developing kidney failure.1 Given its heterogeneous course, a combination of clinical, laboratory, and histopathologic parameters are used to identify patients at risk of poor outcomes.2 Multiple trials have explored the use of corticosteroids and other immunosuppressive medications in high-risk IgAN. The Supportive Versus Immunosuppressive Therapy for the Treatment of Progressive IgA Nephropathy (STOP-IgAN) trial in 2015 compared immunosuppressive therapy (with cyclophosphamide, azathioprine, and/or oral prednisolone) added to a background of optimized renin angiotensin system blockade, compared to supportive care alone.

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)0.011
metaresearch head score (Gemma)0.046
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.015
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.046
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0030.001
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0150.005

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 head0.034
GPT teacher head0.315
Teacher spread0.281 · 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
GenreEditorial

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

Citations2
Published2022
Admission routes2
Has abstractyes

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