The Management of Dietary Fiber Intake in Children With Chronic Kidney Disease – Clinical Practice Recommendations From the Pediatric Renal Nutrition Taskforce
Bibliographic record
Abstract
The benefits of dietary fiber are widely accepted. Nevertheless, a substantial proportion of children fail to meet the recommended intake of dietary fiber. Achieving adequate fiber intake is especially challenging in children with chronic kidney disease (CKD). An international team of pediatric renal dietitians and pediatric nephrologists from the Pediatric Renal Nutrition Taskforce (PRNT) has developed clinical practice recommendations (CPRs) for the dietary intake of fiber in children and adolescents with CKD. In this CPR paper, we propose a definition of fiber, provide advice on the requirements and assessment of fiber intake, and offer practical guidance on optimizing dietary fiber intake in children with CKD. In addition, given the paucity of available evidence and to achieve consensus from international experts, a Delphi survey was performed in which all the clinical practice recommendations were reviewed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".