The Benefits of Temu Mangga (Curcuma Mangga Val) in Cognitive Functions of Elderly
Bibliographic record
Abstract
The objective of this study was to investigate the benefit of Temu Mangga extract (Curcuma Mangga Val) with cognitive function test using Montreal Cognitive Assesment- Indonesian version (MoCA-Ina -Registry MoCA-Ina / stroke registry-INA 2012) in Elderly. This Clinical trial study was conducted using a double-blind, randomized controlled trial, pre and post-test group design in 85 female participants from Panti Wreda Nursing Home in Jakarta. A total of 83 participants who followed the study to the end. 43 participants were administered the Temu Mangga Capsule (TM) group 3x500 mg/day for 30 days. Results: Mean score of MoCA-Ina in TM group increased by 2.37 from 23.93 ± 3.73 to 26.30 ± 3.92 with Wilcoxon test p-value = 0.000, and in the control group with 40 participants increased by 2.55 from 23.58 ± 4.60 to 26.13 ± 4.56 with Wilcoxon test p-value = 0.000. Mann-Whitney test results in both groups p > 0.05. Conclusions: There was an increase in each treatment groups and control groups with significant Moca-Ina values, but between the two groups did not show significant difference changes. Psychological factors such as attention and hope will become healthier are a strong factor in this study.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".