The effects of potatoes and other carbohydrate side dishes consumed with meat on food intake, glycemia and satiety response in children
Bibliographic record
Abstract
BACKGROUND: The effect of carbohydrate (CHO) foods on blood glucose (BG) is ranked by their glycemic index (GI). Boiled and mashed potatoes (BMPs) are ranked as high GI foods, whereas pasta and rice have moderate GI rankings. The objective of this study was to compare ad libitum consumption of common CHO dishes consumed with meat on meal-time food intake and post-meal satiety, BG, insulin and gut hormones in 11- to 13-year-old normal weight children. METHODS: Two randomized crossover studies were conducted. At weekly intervals, children (experiment 1: 12 males (M), 8 females (F); experiment 2: 6M, 6 F) received in random order 1 of 5 CHO side dishes of rice, pasta, BMP, fried French fries (FFF) or baked French fries (BFF) eaten freely together with a fixed amount of lean beef (100 g). In experiment-1, food intake over 30 min and subjective appetite were measured for 120 min. In experiment-2, the same outcomes were measured along with BG, plasma insulin and gut hormones. RESULTS: The results for boys and girls were pooled as sex was not a factor. In both experiments, children consumed 30-40% less calories at meals with BMP (P<0.0001) compared with all other treatments, which were similar. BMP increased satiety, expressed as a change in appetite per kilocalorie, more than all other treatments (P<0.0001). FFF resulted in the lowest (P<0.0001) glucose and insulin at meal end and post-meal and peptide YY (PYY) post-meal. Blood measures were similar among all other treatments. CONCLUSIONS: The physiological functions of CHO foods consumed ad libitum at meal time on food intake, appetite, BG, insulin and gut hormone 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) | 0.002 | 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".