Valorization of plant proteins for meat analogues design—a comprehensive review
Bibliographic record
Abstract
Abstract Animal proteins from meat and its stuffs have recently been one of main concerns in the drive for sustainable food production. This viewpoint suggests that there are exciting prospects to reformulate meat products that are produced more sustainably and may also have health benefits by substituting high-protein nonmeat ingredients for some of the meat. Considering these pre-existing conditions, this review critically reviews recent data on extenders from several sources, including pulses, plant-based components, plant byproducts, and unconventional sources. We used the related keywords from Scopus-database without limiting the publishing date. With an emphasis on how these findings may impact the sustainability of meat products, it sees them as a great chance to enhance the functional quality and technological profile of meat. Therefore, to promote sustainability, meat alternatives such as plant-based meat equivalents are being made available. To boost consumer acceptability of these goods, further initiatives should also be developed to enhance the functioning of these innovative food items and increase public knowledge of plant-based meat analogues.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".