A Brief Review of the Occurrence, Use, and Safety of Food‐Related Nanomaterials
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
Nanotechnology and nanomaterials have tremendous potential to enhance the food supply through novel applications, including nutrient and bioactive absorption and delivery systems; ingredient functionality; improved colors and flavors; microbial, allergen, and contaminant detection and control; and food packaging properties and performance. To determine the current state of knowledge regarding the safety of these potential uses of nanomaterials, an appraisal of the published literature on the safety of food-related nanomaterials was undertaken. A method of assessment of reliability of toxicology studies was developed to conduct this appraisal. The review of the toxicology literature on oral exposure to food-related nanomaterials found that the number of studies is limited. Exposure to nanomaterials in the human food chain may occur not only through intentional uses in food manufacturing, but also via uses in agricultural production and carry over from use in other industries. Although a number of analytical methods are useful in physicochemical characterization of manufactured nanomaterials, new methods may be needed to more fully detect and characterize nanomaterials incorporated into foods and in other media. There is a need for additional toxicology studies of sufficient quality and duration on different types of nanomaterials to further our understanding of the characteristics of nanomaterials that affect safety of oral exposure resulting from use in various food applications.
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 | 0.004 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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