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Record W3024870875 · doi:10.1053/j.ajkd.2020.01.022

Establishing Core Cardiovascular Outcome Measures for Trials in Hemodialysis: Report of an International Consensus Workshop

2020· article· en· W3024870875 on OpenAlexaff
Emma O’Lone, Andrea K. Viecelli, Allison Tong, Bénédicte Sautenet, William G. Herrington, Charles A. Herzog, Tazeen H. Jafar, Vera Krane, Adeera Levin, Jolanta Małyszko, Michael V. Rocco, Giovanni FM Strippoli, Marcello Tonelli, Angela Yee‐Moon Wang, Christoph Wanner, Faı̈ez Zannad, Wolfgang C. Winkelmayer­, David C. Wheeler, Albert Ong, Braden Manns, Roberto Pecoits-Filho, Tess Harris, David C. Wheeler, Adeera Levin, Myra A. Kleinpeter, Angela Ju, Yeoungjee Cho, Talia Gutman, Amélie Bernier-Jean, Laura James, Lorraine Hamiwka, Alan G. Jardine, Bénédicte Stengel, Brigitte Schiller, David W. Johnson, Elena Bavlovlenkov, Fergus Caskey, Barbara S. Gillespie, Geoffrey A. Block, Hai An Ha Phan, Hiddo J.L. Heerspink, Magdalena Madero, Marinella Ruospo, Mark L. Unruh, Maurice Laville, Nisha Bansal, Patrick B. Mark, Peter J. Blankestijn, Prabir Roy‐Chaudhury, Rachel Perlman, Rajiv Agarwal, Rajnish Mehrotra, Stephen L. Seliger, Tariq Shafi, Thomas F. Hiemstra, Vanita Jassal, Vlado Perkovic, Amanda Simplice, David M. White, Denise Eilers, Caroline Wilkie

Bibliographic record

VenueAmerican Journal of Kidney Diseases · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
FundersNational Health and Medical Research CouncilMedical Research CouncilKidney Research UK
KeywordsMedicineHemodialysisIntensive care medicinePopulationMyocardial infarctionDiseaseClinical trialNephrologyInternal 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)0.694
metaresearch head score (Gemma)0.564
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.306
Threshold uncertainty score0.377

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6940.564
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0180.017
Bibliometrics0.0100.010
Science and technology studies0.0040.006
Scholarly communication0.0170.012
Open science0.0190.018
Research integrity0.0150.034
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 head0.454
GPT teacher head0.461
Teacher spread0.008 · 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 designNot applicable
DomainMethods
GenreMethods

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

Citations18
Published2020
Admission routes1
Has abstractno

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Same venueAmerican Journal of Kidney DiseasesSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207