Smaller dishware to reduce energy intake: fact or fiction?
Bibliographic record
Abstract
The potential effects of dishware size on energy intake are unclear, as many previous studies have been of low methodological quality. A newly published paper by Kosīte et al. (IJBNPA 10.1186/s12966-019-0826-1, 2019) reports findings from a rigorous, pre-registered investigation of the effects of manipulating plate size on total energy intake within a single eating occasion. This Editorial considers the implications of these new findings in light of previous evidence pertaining to the efficacy of behavioral nudges in particular, and in relation to contextual drivers of food consumption more generally. We conclude that the potential impact of behavioral nudges may have been exaggerated in the past, and call for future high-quality randomized controlled trials to establish whether reducing dishware size and other behavioral nudges might offer an effective complement to more comprehensive, multi-level interventions to reduce overconsumption of foods and beverages at a population-level.
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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 | 0.007 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.025 | 0.027 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".