Microbiological Safety Levels of South Sudanese Bank Notes in Circulation at University of Juba Food Restaurants
Bibliographic record
Abstract
Food borne infections arise from either a host of bacteria, viruses and parasites originating in food or pathogens introduced through cross contamination. This study assessed the potential microbiological cross contamination risk posed by South Sudanese Pounds in circulation at University of Juba food restaurants by examining the level of microorganisms on banknotes. Bacterial contamination on the South Sudanese Pounds in circulation at University of Juba were determined using currencies collected from five different food serving points coded A,B,C, D and E respectively. From each food serving points, five samples of banknotes 5, 10and 25 South Sudanese Pounds denominations were randomly selected and their surface bacterial content enumerated. High and varying proportions of Total Coli forms (TC), Escherichia coli (E. Coli) and Staphylococcus aureus (S. aureus) were detected. Findings revealed a significant correlation between microbial levels and the denominations of the bank notes, with the smallest having the highest levels of microorganisms per square centimeter. However, there was no specific pattern in contamination levels between banknotes obtained from the different food points. Another factor that influenced the level of contamination was period the banknotes took in circulation with the older notes having higher levels of microorganisms. High levels of microorganisms on banknotes coupled with unhygienic food handling practices predisposes consumers to health risks. Strategies to reduce the risk of transmission of pathogens from the South Sudanese Pounds with specific emphasis on awareness programs and improvement in food hygiene & handling practices through physical contact between food and money in restaurants at University of Juba were mentioned in order to reduce risk of food borne illness or otherwise potentially lethal outbreak of food borne diseases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".