Should an anti-inflammatory diet be used in long-term care homes?
Bibliographic record
Abstract
Background: Inflammation is associated with the pathogenesis of several age-related chronic conditions such as diabetes, cardiovascular disease, arthritis and dementia. Most older adults residing in long-term care (LTC) homes have at least one of these conditions; they also have some degree of compromised nutritional intake due to management, personal and medical challenges. We hypothesized that an anti-inflammatory diet in LTC is necessary and feasible, and may lead to improvements in the health and wellbeing of residents. Methods: A literature review was carried out to evaluate the evidence on effectiveness of anti-inflammatory diet changes in adults as well as the feasibility of LTC menu revision. Results: Dietary components have both positive and negative influences on inflammation in older adults. LTC menu revisions using the anti-inflammatory diet popularized by Weil, which is designed as a food guide, are feasible. This diet could be used in LTC menu planning to complement and expand upon Canada’s Food Guide recommendations. Conclusions: Implementation of a nutrient-dense, anti-inflammatory diet may lead to improved health and wellbeing among LTC residents.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".