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Record W4399557068 · doi:10.1053/j.jrn.2024.05.008

The Management of Dietary Fiber Intake in Children With Chronic Kidney Disease – Clinical Practice Recommendations From the Pediatric Renal Nutrition Taskforce

2024· article· en· W4399557068 on OpenAlexaff
An Desloovere, Nonnie Polderman, José Renken‐Terhaerdt, Vanessa Shaw, Caroline Anderson, Larry A. Greenbaum, Christina L. Nelms, Leila Qizalbash, Stella Stabouli, Jetta Tuokkola, Bradley A. Warady, Johan Vande Walle, Fabio Paglialonga, Rukshana Shroff, Evelien Snauwaert

Bibliographic record

VenueJournal of Renal Nutrition · 2024
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsBC Children's Hospital
FundersNational Institute for Health and Care ResearchEuropean Rare Kidney Disease Reference NetworkDepartment of Health and Social CareVitaflo
KeywordsMedicineKidney diseaseDietary fiberClinical PracticeDietary managementIntensive care medicineDiseaseKidneyInternal medicineEnvironmental healthFamily medicineFood science

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.500
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.366
Teacher spread0.336 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2024
Admission routes1
Has abstractno

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