Segurança alimentar e fortificação de alimentos à base de polpa de café em tempos de pandemia
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic caused human losses, tensions in medical care, the economy and other social systems. Objective: To collect information on food safety and fortification of foods based on coffee pulp, considering that good nutrition counteracts infections. Methodology: Literature in SciELO and SCOPUS bases was analyzed, restricting search terms to food safety, COVID-19, block chain technology, food supply, micronutrients, regulation, iron fortification with emphasis on coffee pulp-based products. Results: In times of pandemic and other disasters, one of the factors that affect the response of a host to the virus is nutrition. The importance of food security is recognized with proposals especially in countries with high rates of malnutrition and anemia, for the fortification of common foods to contribute to guaranteeing nutritional adequacy as part of the governments’ responses, especially in impoverished rural and urban areas, considering food supply systems with block or Block Chain technology. Conclusion: The fortification of food products based on coffee pulp and their supply using block chain could be a response strategy to the consequences of the pandemic.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".