Increased portion size leads to a sustained increase in energy intake over 4 d in normal-weight and overweight men and women
Bibliographic record
Abstract
Large food portions may be facilitating excess energy intake (EI) and adiposity among adults. The present study aimed to assess the extent to which EI and amounts of foods consumed are influenced by the availability of different-sized food portions. A randomised within-subject cross-over, fully residential design was used, where forty-three (twenty-one men and twenty-two women) normal-weight and overweight adults were randomly allocated to two separate 4 d periods where they were presented with either 'standard' or 'large' food portions of the same foods and beverages. The main outcome measures were the amount of food (g) and EI (MJ) consumed throughout each study period. Mean EI over 4 d was significantly higher on the large portion condition compared with the standard condition in the total group (59.1 (sd 6.6) v. 52.2 (sd 14.3) MJ; P = 0.020); men and women increased their EI by 17 % (10 (sd 6.5) MJ; P < 0.001) and 10 % (4 (sd 6.5) MJ; P = 0.005) respectively when served the large food portions relative to the standard food portions. The increased intakes were sustained over the 4 d in the large portion condition with little evidence of down-regulation of EI and food intake being made by subjects. Increased food portion size resulted in significant and sustained increases in EI in men and women over 4 d under fully residential conditions. The availability and consumption of larger portions of food may be a significant factor contributing to excess EI and adiposity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".