Potential of Functional Factors in Foods for 3D Printing to Manage Metabolic Syndrome: A Comprehensive Review
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
Dietary therapy has emerged as an adjunctive therapeutic strategy for the management of metabolic syndrome. However, traditional means of food processing are not able to meet the specific taste, nutritional, and emotional value needs of people with metabolic syndrome. The emergence of 3D food printing technology has led to breakthroughs in the creation of customized and personalized food products. This paper provides a systematic review of functional ingredients in foods suitable for controlling metabolic syndrome and their potential applications in 3D printing. In addition, it evaluates the impact of pretreatment and post-treatment technologies on the printability of these functional materials as well as the quality of printed products. Finally, the potential application of artificial intelligence and big data in helping to manage metabolic syndrome is explored, as well as its role in guiding and supporting 3D food printing. This review aims to provide theoretical support for future research on functional foods.
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