The Impact of COVID-19 Pandemic on Seafood Safety and Human Health
Bibliographic record
Abstract
The coronavirus disease (COVID-19) pandemic caused several negative impacts on global human health and the world's economy. Food and seafood safety and security were among the principal challenges and causes of concern for the food industry and consumers during the spread of this global pandemic. This article focused on the effects of COVID-19 pandemic on potential safety issues with seafood products and their processing methods. Moreover, the potential impacts of coronavirus transmission through seafood on human health were evaluated. The role of authenticity, traceability, and antimicrobials from natural sources to preserve seafood and the possible interaction of functional foods on the human immune system are also discussed. Although seafood is not considered a principal vector of SARS-CoV-2 transmission, the possible infections through contaminated surfaces of such food products cannot be neglected. The positive effects of seafood consumption on possible immunity built up, and COVID-19 are also summarized.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".