Review of Nutritional Components and Health Benefits of Sweet Potato
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sweet potatoes ( Ipomoea batatas ) have received increasing attention in recent years due to their high nutrition and the variety of active substances they contain. In this article, we have sorted out the main components of different parts of sweet potatoes, such as leaves and roots, and focused on introducing dietary fiber, beta-carotene, anthocyanins, vitamin C, minerals, etc., as well as the possible benefits they may bring to health. Nowadays, there are numerous in vitro experiments, animal experiments, and A small number of human studies, all of which show that eating sweet potatoes may have many benefits, such as improving vitamin A status, regulating blood sugar and lipid levels, antioxidation, anti-inflammation, protecting the cardiovascular system, anti-cancer, and even helping intestinal health. Generally speaking, sweet potatoes with orange flesh contain A lot of beta-carotene, which is helpful in preventing vitamin A deficiency. Purple sweet potatoes have a high content of anthocyanins and a stronger antioxidant effect. Sweet potato leaves themselves are also a good source of protein, minerals and polyphenols, and have high nutritional value. Although sweet potatoes have been regarded as a crop with high nutritional density and the ability to promote health, there are still not enough high-quality human clinical studies at present. The mutual influence among different genotypes, environmental conditions and processing methods also requires further research. In the future, cooperation among different disciplines should be strengthened to enable sweet potatoes to play a greater role in functional foods, nutritional intervention and breeding, and to promote more innovation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it