Bibliographic record
Abstract
This study aims to identify the effectiveness of malnutrition intervention programs within senior populations. Government subsidized nutrition intervention programs, such as Meals on Wheels, play a vital role in the prevention of malnutrition in lower socioeconomic senior populations in the United States (Roy, 2006). For many older adults, meals received via nutrition programs serve as a lifeline, meeting essential nutritional needs and preventing premature institutionalized care (Lepore, 2019). Sixty-three Meals on Wheels (MOW) participants residing in Southern California were assessed, comparing nutritional status upon program intake against nutritional status after three to six months to identify improvement or decline. This study relied on self-reporting on the part of senior participants to explore the characteristics related to socioeconomic status and nutritional risk, and collect quantitative data. Further, it aimed to highlight whether nutritional risk was decreased through program usage. Access to the MOW nutrition program was found to correlate with a reduction in malnutrition risk among the participants in the study. Through the use of nutrition programs and their evaluations, malnutrition and malnutrition risk may be detected earlier, and subsequent measures for prevention can be employed.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".