Recent Advances and Potential Applications of Atmospheric Pressure Cold Plasma Technology for Sustainable Food Processing
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
In a circular economy, products, waste, and resources are kept in the system as long as possible. This review aims to highlight the importance of cold plasma technology as an alternative solution to some challenges in the food chain, such as the extensive energy demand and the hazardous chemicals used. Atmospheric cold plasma can provide a rich source of reactive gas species such as radicals, excited neutrals, ions, free electrons, and UV light that can be efficiently used for sterilization and decontamination, degrading toxins, and pesticides. Atmospheric cold plasma can also improve the utilization of materials in agriculture and food processing, as well as convert waste into resources. The use of atmospheric cold plasma technology is not without challenges. The wide range of reactive gas species leads to many questions about their safety, active life, and environmental impact. Additionally, the associated regulatory approval process requires significant data demonstrating its efficacy. Cold plasma generation requires a specific reliable system, process control monitoring, scalability, and worker safety protections.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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