The Effects of Potatoes and other Carbohydrate Side Dishes on Meal Time Food Intake, Blood Glucose and Satiety Response in Lean Healthy Children
Bibliographic record
Abstract
Background The effect of carbohydrate foods on blood glucose is ranked by their glycemic index. Boiled‐mashed‐potatoes (BMP) are ranked as high GI but pasta and rice have moderate GI ranking. Objectives To compare ad libitum consumption of common carbohydrate dishes on meal‐time satiety, food‐intake blood glucose and insulin in 11 to 13 year normal weight children. Methods Two studies were conducted. At weekly intervals, children (experiment‐1: 12M, 8F; experiment‐2: 6M, 3F) randomly received 1 of 5 ad libitum carbohydrate meals of rice, pasta, BMP, fried‐french‐fries (FFF) or baked‐french‐fries (BFF) together with 100g lean beef as a lunch time meal. In experiment‐1, food intake over 30 minutes and subjective appetite was measured for120 minutes. In experiment‐2, the same outcomes were measured along with blood glucose and plasma insulin. Results The results for both boys and girls were pooled as sex was not a factor(P=0.51). In both experiments, children consumed the 30% less calories at meals with BMP(P<0.0001) compared to all other treatments, which were similar. Expressed as a change in appetite per kilocalorie, BMP lowered appetite more than all other treatments(P<0.0001). In experiment‐2, FFF resulted in the lowest(P<0.0001) end of meal glucose and insulin concentrations at 30 min. Conclusion The role of carbohydrate foods consumed ad libitum at meal time on food intake, appetite, blood glucose and insulin responses in children is not predicted by the GI.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".