Consumption of dewaxed brown rice for a six-month period improves cognitive function in older adults: an open-label trial
Bibliographic record
Abstract
Brown rice has received attention for its potential to improve cognitive function, but evidence from human subjects is scarce. Therefore, we conducted an open-label trial to examine the effectiveness of consuming low doses of dewaxed brown rice for six months in improving or maintaining cognitive function in older adults without cognitive impairment. Fifty-six cognitively healthy older people (≥60 years old) were recruited for this study; participants were divided into groups (consuming dewaxed brown rice or white rice) and asked to consume each type of rice four times per week for six months. We evaluated cognitive function before and after the intervention period to examine the effects of consuming dewaxed brown rice on cognitive function. Our analyses showed that the total score on the Frontal Assessment Battery was improved in the brown-rice group but not in the white-rice group. Post-hoc analysis demonstrated that the total score on the Frontal Assessment Battery improved in the brown rice group but not the white rice group after intervention. In contrast, the total score on the Mini-Mental State Examination was not changed in either group. These findings suggest that consuming low doses of dewaxed brown rice improved executive function in older people.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".