Protein requirements in healthy school‐age children determined by using the indicator amino acid oxidation technique
Bibliographic record
Abstract
Protein (PRO) requirements in school‐age children were determined by the indicator amino acid oxidation (IAAO) method. Four, healthy children (8 – 11 yr) each randomly received a minimum of three PRO intakes below 0.9 and three intakes above 0.9 g/kg/d; range = 0.16 – 1.84 g/kg/d. The diets were isocaloric and provided energy at 1.7 X REE. PRO was given as an amino acid mixture based on egg protein composition, except phenylalanine which was maintained constant across intakes. PRO requirements were determined by measuring the oxidation of L‐[1‐ 13 C]‐phenylalanine to 13 CO 2 ( F 13 CO 2 ). Breath and urine samples were collected at baseline and isotopic steady state. Linear regression crossover analysis identified a breakpoint (requirement) at minimal F 13 CO 2 in response to different PRO intakes. Preliminary results indicate the mean and population‐safe PRO requirements to be 1.35 and 1.59 g/kg/d, respectively. These results are significantly higher than the mean and population‐safe PRO requirements of 0.76 and 0.95 g/kg/d, respectively, currently recommended by the Dietary Reference Intakes (DRI 2005) for macronutrients This study is the first to directly estimate protein requirements in children and suggests that the current recommendations, based on a factorial method are severely underestimated. (CIHR supported)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".