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Record W2797187174 · doi:10.1053/j.ajkd.2017.12.011

Estimating Time to ESRD in Children With CKD

2018· article· en· W2797187174 on OpenAlexaff
Susan L. Furth, Chris Pierce, Wun Fung Hui, Colin White, Craig S. Wong, Franz Schaefer, Elke Wühl, Alison G. Abraham, Bradley A. Warady, Joshua Samuels, Meredith A. Atkinson, Amy C. Wilson, Alejandro Quiroga, Susan F. Massengill, Dave Selewski, María Ferris, Amy J. Kogon, Frederick J. Kaskel, Marc B. Lande, George J. Schwartz, Jeffrey M. Saland, Victoria F. Norwood, Tej Matoo, Guillermo Hidalgo, Poyyapakkam Srivaths, Joann Carlson, Craig B. Langman, Susan R. Mendley, Eunice John, Kiran Upadhyay, Patricia Seo-Mayer, Larry T. Patterson, Rulan S. Parekh, Lisa Robinson, Adam Weinstein, Dmitry Samsonov, Juan C. Kupferman, Jason Misurac, Anil Mongia, Steffan Kiessling, Cheryl Sanchez-Kazi, Allison Dart, Sahar Fathallah, Donna Claes, Mark Mitsnefes, Tom Blydt‐Hansen, Larry A. Greenbaum, Joseph T. Flynn, Isidro B. Salusky, Ora Yadin, Katherine M. Dell, Randall Jenkins, Cynthia G. Pan, Elaine Ku, Amira Al‐Uzri, Nancy Rodig, Cynthia Wong, Keefe Davis, Martin A. Turman, Sharon Bartosh, Colleen Hastings, Anjali Nayak, Mouin G. Seikaly, Nadine Benador, Robert H. Mak, Ellen G. Wood, Gary Lerner, Gina Marie Barletta, Ali Anarat, Ayşı̇n Bakkaloğlu, Fatih Özaltın, Amira Peco‐Antić, Uwe Querfeld, Jutta Gellermann, P. Sallay, Dorota Drożdż, Klaus-Eugen Bonzel, Anne‐Margret Wingen, Aleksandra Żurowska, I Bałasz, Antonella Trivelli, Francesco Perfumo, D. Muller-Wiefel, Kirsten Møller, G. Offner, Barbara Enke, Charlotte Hadtstein, Otto Mehls, Sevinç Emre, S. Mir, Simone Wygoda, Katharina Hohbach-Hohenfellner, N Jeck, Günter Klaus, Gian Luigi Ardissino, Sara Testa, Giovanni Montini, Marina Charbit, Patrick Niaudet, Alberto Caldas Afonso, Ana Fernandes-Teixeira, Ladislav Dušek, Maria Chiara Matteucci, Stefano Picca, Antonio Mastrostefano, Marianne Wigger, U. Berg, Giovanni Celsi, Michel Fischbach, Janoš Terzić, J Fydryk, Tomasz Urasiński, Rosanna Coppo, Licia Peruzzi, Klaus Arbeiter, A. Jankauskiené, Ryszard Grenda, Mieczysław Litwin, Roman Janas, T. Neuhaus

Bibliographic record

VenueAmerican Journal of Kidney Diseases · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicineRenal functionKidney diseaseGuidelineProteinuriaCreatinineInternal medicineCohortCohort studyUrologyRenal replacement therapyKidneyPathology

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)0.001
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.247
Teacher spread0.244 · 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

Citations91
Published2018
Admission routes1
Has abstractno

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