Nutritional and Antioxidant Properties of Porphyra spp.: Implications for Human Health
Bibliographic record
Abstract
Porphyra spp. is a widely edible marine red algae that has attracted much attention for its rich nutritional value and significant antioxidant activity. This study systematically analyzes the nutritional composition, functional compounds and their antioxidant properties of seaweed, and explores the potential benefits of seaweed intake for human health. Seaweed has high protein content, complete types of essential amino acids and appropriate proportions; it is rich in carbohydrates and dietary fiber, and has significant vitamins and minerals. Seaweed is rich in functional ingredients such as polyphenols, carotenoids, phycobilidins and sulfate polysaccharides, making it have significant antioxidant activity and a variety of biological functions. Studies have shown that seaweed extract has the ability to scavenge free radicals and may play an active role in anti-inflammatory, immune regulation, cardiovascular health protection, as well as anti-tumor and anti-aging. This study sorts out the results of research on nutrition and function of seaweed in recent years and discusses future research and application directions.
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 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".