Evaluation of Supplementation of Ashgourd Fermented Beverage to Geriatric Population
Bibliographic record
Abstract
Existing data indicates a significant morbidity among the aged and most may remain subclinical. Vegetables being good source of vitamins and minerals, further their concentration has been improved by fermentation process. In recent years elderly institutions are being more common and a need for nutritional studies to provide better service. Thus the present study was conducted on geriatrics population to see the effect of ashgourd fermented beverage on anthropometric, nutritional and biochemical status of institutional elderly inmates. Ashgourd Fermented beverage (180ml) was provided to inmates of experimental group with the instructions to drink in fasting condition as a first drink in the morning for 60 days and control group received no supplementation. The parameters which were selected to evaluate the effect of ashgourd fermented beverage were anthropometric data, nutritional status, dietary pattern, clinical, biochemical parameters such as fasting and post prandial blood glucose levels, lipid profile, haemoglobin level and medical histories of the inmates. The selected parameters were assessed before and after the supplementation to see the effect of fermented beverage. It can be concluded from the present study that supplementation of fermented beverage showed significant improvement in BMI grades, heamoglobin and reduced blood glucose level, triglycerides and improved HDL cholesterol levels in experimental group when compared with the control group.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 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".