Cell-based fish production case study for developing a food safety plan
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
Given the expanding global population and finite resources, it is imperative to explore alternative technologies for food production. These technologies play a crucial role in ensuring the provision of safe, nutritious, and sustainable food options to meet the growing demand. Cellular agriculture plays an important in developing an alternative method for developing food products. While, cellular agriculture is emerging rapidly, food safety aspects and regulatory frameworks stayed behind. Despite developing several regulatory framework papers on cellular agriculture, there is no systematic approach for developing a comprehensive food safety plan (FSP), particularly for cultivated seafood. Thus, the overall goal of this article is to develop a FSP for cultivated seafood. The main differences between the food safety plan for cultivated seafood and the conventional seafood industries were the number of allergens in cultivated seafood products, including soy, wheat, and fish cells, compared to only fish for the conventional seafood industry. In addition, there are several hazards associated with mycoplasma in cultivated seafood, which should be considered. This guidance intends to help regulatory agencies, food safety experts, startup companies, and the cultivated seafood industry by providing a valuable platform to develop regulations, guidance, and food safety plans applicable to most cultivated seafood companies. This article will also help the industry to identify the hazards in their processing line and develop preventive controls, and as a comprehensive food safety plan, it could be easily adapted for other cultivated seafood products. This guidance applied systematic approaches to developing food safety plans using cell culture, pharmaceuticals, fermentation, seafood, meat, and aquaponics safety plans, collaborating with experts with different backgrounds, and working closely with the conventional and cultivated meat and seafood industries.
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