Evaluating the Effect of Applying the FDA Definition of Whole Grains to Health Claims for Risk Reduction of Cardiovascular Disease and Diabetes
Bibliographic record
Abstract
The U.S. Food and Drug Administration (FDA) defines whole grains as consisting of the intact, ground, cracked or flaked fruit of the grains whose principal components‐the starchy endosperm, germ and bran‐are present in the same relative proportions as they exist in the intact grain. We evaluated the effect of applying the FDA definition of whole grains on the strength of scientific evidence in support of claims for risk reduction of cardiovascular disease (CVD) and diabetes. We concluded that using the FDA definition for whole grains as a selection criterion is limiting because the majority of existing studies often use a broader meaning to define whole grains. When considering only whole grain studies that met the FDA definition we found insufficient scientific evidence to support a claim that whole grain intake reduces the risk of CVD. However, a whole grain and CVD health claim is supported when using a broader concept of whole grain to include studies that included intake of bran and germ as well as whole grain. The scientific evidence on the relationship of whole grain consumption and diabetes is suggestive but inconclusive whether or not the definition of whole grains was in accordance with that of the FDA. This type of analysis is complicated by variation among different types of whole grains due to their diversity in nutrients and bioactive components. This project was sponsored by Kellogg Company, USA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.258 | 0.510 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".