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Record W4406845874 · doi:10.1016/j.ekir.2024.11.383

WCN25-1638 ALIGN SUBGROUP ANALYSES: CLINICALLY MEANINGFUL UPCR REDUCTIONS SEEN ACROSS SUBGROUPS

2025· article· en· W4406845874 on OpenAlexaff
Donald E. Kohan, Richard Lafayette, Adeera Levin, Adrian Liew, Hong Zhang, Todd Gray, Khushboo Sheth, Ronny Renfrum, Hetal S. Kocinsky, Jonathan Barratt

Bibliographic record

VenueKidney International Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineSubgroup analysisInternal medicineMeta-analysis

Abstract

fetched live from OpenAlex

Approximately 30% of IgAN patients with proteinuria 1–2 g/day develop kidney failure within 10 years; even patients with low levels of persistent proteinuria (<1 g/day) are at risk. Endothelin (ET)-1 upregulation and ETA receptor activation drive proteinuria, kidney inflammation and fibrosis in IgAN. Atrasentan is a potent and selective ETA receptor antagonist. ALIGN is a Phase 3, randomized, double-blind, placebo-controlled study of the efficacy and safety of atrasentan vs placebo in adult IgAN patients on optimized supportive care.

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)0.006
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.054
GPT teacher head0.455
Teacher spread0.401 · 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

Citations0
Published2025
Admission routes1
Has abstractno

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