Portion‐size preference as a function of individuals' body mass index
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Large portions of food are often blamed for rising rates of obesity. We tested the possibility that people who are heavier may tend to select or prefer larger portions than do people who are lighter. METHODS: = 798) were asked to choose between a small and larger portion of pasta for a hypothetical meal (Studies 1, 2 and 4), to indicate their ideal portion from a range of portion-size options (Study 2), or to select their preferred portion size from each of 28 portion pairs (Study 3). RESULTS: = -0.06 to 0.33). The pattern was the same regardless of whether we grouped participants as having a body mass index (BMI) <25 vs. ≥25, as having a BMI of <30 vs. ≥30, or treated BMI as a continuous predictor. CONCLUSIONS: Given the lack of association between BMI and portion-size preference, we suggest that factors other than portion size, such as differences in meal frequency, food type, plate clearing or compensation at subsequent meals, may need to be considered in order to explain the increasing prevalence of obesity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it