Enhancing Curcumin and Mineral Content in Red Turmeric via Magnetic Field Exposure
Bibliographic record
Abstract
The public needs curcumin because it has strong anti-inflammatory and antioxidant effects. As the human population increases, agricultural land decreases. Increasing the curcumin content in red turmeric is necessary to maintain its availability. This research aims to optimize production results and red turmeric's curcumin, magnesium, iron, and oxalic acid content. This research uses a magnetic field (MF) whose magnetic flux density (MFD) changes over time; the exposure time was 20 minutes and repeated every day for five days. The results showed that exposure to 0.2 mT MFD increased production by 42.96% and iron content by 13.20%. Exposure to 0.3 mT MFD increased curcumin content by 85.95% and magnesium by 33.39%. Exposure to 0.7 mT MFD increased the oxalic acid content by 4.04%. Not all essential substances contained in turmeric change due to MF processing. Using MF with an MFD that changes over time requires a low value
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 | 0.000 | 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) | 0.000 | 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".