Effect of Commercially Available Sugar-Sweetened Beverages on Subjective Appetite and Short-Term Food Intake in Girls
Bibliographic record
Abstract
Background: The effect of sugar-sweetened beverages (SSBs) on satiety and short-term food intake (FI) regulation in girls has received little attention. The objective of the present study was to compare the effect of pre-meal consumption of commercially available SSBs on subjective appetite and short-term FI in 9–14-year-old girls. The methods we used include using a randomized crossover design in which 28 girls consumed isovolumetric amounts (350 mL) of a fruit drink (154 kcal), cola (158 kcal), 1% chocolate milk (224 kcal), or water (control; 0 kcal) on four separate mornings. Subjective appetite and thirst were measured at regular intervals via visual analogue scales (VAS) and FI was assessed at 60 min post-beverage consumption. The results show that subjective appetite and thirst decreased after all beverages, but did not differ among beverages. Short-term FI was suppressed following consumption of chocolate milk (15%; p < 0.001) and cola (11%; p = 0.02) compared to the water control. However, cumulative energy intake (beverage (kcal) + test meal (kcal)) was not affected by beverage type. In conclusion, chocolate milk and cola, but not fruit drink, suppressed FI in girls while cumulative FI did not differ among treatments.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.002 | 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".