Microbiological quality of ready to eat coleslaw marketed in Ibadan, Oyo-State, Nigeria
Bibliographic record
Abstract
This study assessed the microbiological quality of coleslaw samples sold at restaurants in Ibadan, Oyo-state, Nigeria. Three hundred and sixty samples were analyzed over a 12-week period for aerobic mesophilic counts, psychrotrophic counts, levels of Enterobacteriaceae, yeasts and molds, total lactic acid bacteria and total anaerobes. The coleslaw samples were also analyzed for presumptive L. monocytogenes and Salmonella spp. Counts of up to 9.2, 8.2, 9.4, 9.0, 8.7, and 8.9 log CFU/g for aerobic mesophilic organisms, psychrotrophic counts, Enterobacteriaceae, yeasts and molds, total lactic acid bacteria and total anaerobes, respectively, were recovered from the coleslaw samples. Despite high counts of yeasts and molds and LAB (up to 9 and 8.7 log CFU/g, respectively) recovered from some samples, no visible spoilage was detected. The levels of microorganisms recovered from the coleslaw samples at different sample collection time (week 1–12) were significantly (P < 0.05) different for each restaurant. Similarly, microbial levels recovered from coleslaw samples collected from different restaurants differed significantly (P < 0.05) from one restaurant to the other. Thirty (30.5%) and 24.7% of the coleslaw samples were positive for presumptive L. monocytogenes and Salmonella, respectively, an indication of potential threats to food safety in the area. The study concluded that the roles of yeasts and molds, as well as LAB in the spoilage of coleslaw sold in the study area, need to be further investigated. Public health intervention strategies to enhance microbiological safety of RTE coleslaw are required in the city.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".