Barriers to Innovation in the field of Food Nanotechnology Applications within the European Union
Bibliographic record
Abstract
Nanotechnology is deemed to be one of the key technologies of the 21st century. It is an area of emerging interest and opens new possibilities for the food industry, including uses in food products, processing and packaging. The market for nanotechnology-derived products for the food sector is predicted to grow rapidly in the coming years. Research activities on applications of nanotechnology in the food sector already include development of improved taste, color, flavor, texture and consistency of food products, increased absorption and bioavailability of nutrients and bioactive compounds, improved quality, shelf-life and safety of food products due to new food packaging materials with improved mechanical, barrier and antimicrobial properties, and nano-sensors for traceability and monitoring the condition of food during transport and storage. Beside technical and safety issues, regulatory and analytical challenges as well as public perception have been identified as barriers to innovation in the field of food nanotechnology applications within the European Union. Nanotechnology has already provoked public concern and debate and is hailed by scientists and corporations for their potential and criticized by environmental and consumer groups because of their risks. Public concern about food nanotechnology applications include a lack of transparency and choice about exposure, risks to health and environment, unfair distribution of risks and benefits and a lack of socially useful applications. It is significant that public concerns extend beyond narrowly defined issues of scientific risk to broader questions over the control, purpose and predictability of nanotechnology's application.
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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 | 0.035 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".