Microalgae Proteins as Sustainable Ingredients in Novel Foods: Recent Developments and Challenges
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
Microalgae are receiving increased attention in the food sector as a sustainable ingredient due to their high protein content and nutritional value. They contain up to 70% proteins with the presence of all 20 essential amino acids, thus fulfilling human dietary requirements. Microalgae are considered sustainable and environmentally friendly compared to traditional protein sources as they require less land and a reduced amount of water for cultivation. Although microalgae's potential in nutritional quality and functional properties is well documented, no reviews have considered an in-depth analysis of the pros and cons of their addition to foods. The present work discusses recent findings on microalgae with respect to their protein content and nutritional quality, placing a special focus on formulated food products containing microalgae proteins. Several challenges are encountered in the production, processing, and commercialization of foods containing microalgae proteins. Solutions presented in recent studies highlight the future research and directions necessary to provide solutions for consumer acceptability of microalgae proteins and derived products.
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.
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 it