Effect of potatoes and other carbohydrate-containing foods on cognitive performance, glycemic response, and satiety in children
Bibliographic record
Abstract
Dietary carbohydrates have been shown to influence cognitive performance and satiety in children. However, it remains unclear whether the carbohydrate source is a primary determinant of cognitive performance and satiety. The objective was to compare the effects of white potatoes and other carbohydrate-containing foods on cognitive performance, glycemic response, and satiety in children. On 6 separate mornings, in random order, children (n = 22) consumed 50 g of available carbohydrates from microwaved mashed potatoes (prepared from fresh potatoes then frozen), deep-fried potato strips (French fries), hash browns, white rice, white beans, or skipped a meal. Cognitive performance, glycemic response, and satiety were measured over 180 min. Cognitive performance was measured using a battery of tests assessing verbal declarative memory, spatial memory, short-term memory, working memory, and information processing speed. Although cognitive performance after the treatment meals did not differ from meal skipping, children recalled more words after French fries (9.1 ± 0.4 words) compared with mashed potatoes (8.2 ± 0.3 words; p = 0.001) and white rice (8.4 ± 0.3 words; p = 0.04) on the verbal declarative memory test. Blood glucose concentrations were higher after white rice compared with white beans, mashed potatoes, and hash browns (p < 0.05). Change from baseline subjective average appetite (mm/kcal) was lower after mashed potatoes compared with all other treatment meals (p < 0.05). In conclusion, verbal declarative memory was higher after French fries and subjective average appetite was lower after mashed potatoes. Future longitudinal studies are needed to confirm these short-term findings and to elucidate the mechanism of action.
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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 | 0.002 |
| 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 | 0.000 |
| 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".