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Record W4406692140 · doi:10.1053/j.ajkd.2024.10.013

A Core Outcome Set for Trials in CKD: Report of the Standardized Outcomes in Nephrology–Chronic Kidney Disease (SONG-CKD) Stakeholder Workshops

2025· article· en· W4406692140 on OpenAlexaff
Andrea Matus González, Rosanna Cazzolli, Magdalena Madero, Nicole Evangelidis, Martin Howell, Bénédicte Sautenet, Amélie Bernier-Jean, Yeoungjee Cho, Laura Cortés Sanabria, Jonathan C. Craig, Ian H. de Boer, Samuel Fung, Daniel Gallego, Chandana Guha, Jenny I. Shen, Andrew S. Levey, Adeera Levin, Eduardo Lorca, Sebastián Cabrera, Haydee Mellado, S Olivan Molina, Ximena Atilano, Lorena Sandino, Macarena Arancibia, Marcelo Urra, María Carmen Bravo, Karine Manera, Javier Recabarren, Ikechi G. Okpechi, Patrick Rossignol, Nicole Scholes‐Robertson, Laura Solà, Armando Teixeira‐Pinto, Tim Usherwood, Andrea K. Viecelli, David C. Wheeler, Katherine Widders

Bibliographic record

VenueAmerican Journal of Kidney Diseases · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of British Columbia
FundersNational Health and Medical Research CouncilAgencia Nacional de Investigación y DesarrolloInternational Society of Nephrology
KeywordsMedicineKidney diseaseNephrologyInternal medicineIntensive care medicineCore (optical fiber)Outcome (game theory)Family medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.550
metaresearch head score (Gemma)0.590
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.450
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5500.590
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0050.004
Science and technology studies0.0030.002
Scholarly communication0.0050.005
Open science0.0040.015
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.231
GPT teacher head0.498
Teacher spread0.267 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations8
Published2025
Admission routes1
Has abstractno

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