Growth Behavior of Listeria monocytogenes during over 60-Day Ripening of Camembert Cheeses Produced by Unpasteurized Raw Milk
Bibliographic record
Abstract
Although the USA, Canada, and several EU countries allow raw milk cheese to be aged more than 60 days, these countries have strict standards for its aging conditions, such as temperature. Many developed countries have employed standards of identity which effectively prevent the manufacture and sale, of cheese made from unpasteurized milk (i.e., raw milk) in interstate commerce, unless such cheese has been aged for a minimum of 60 days. The microbiological safety of raw milk Camembert cheese, aged for more than 60 days, was evaluated using spiking experiments. We spiked Listeria monocytogenes into raw milk with different inoculation levels (high, medium and low). Camembert cheese was prepared from the inoculated raw milk, then aged in an incubator for up to 9 weeks (63 days). The number of cells was determined every week using the agar-plating method. Inoculated cells were completely eliminated, especially in Camembert cheese, after 60 days, and the reduction rate of cells was much faster in Camembert cheese. There were no significant differences in pH and water activity (aW) between the uninoculated cheese and the cheese samples in which Listeria monocytogenes was inoculated (p<0.05). The pH and aW of the Camembert cheese decreased throughout the storage period. In conclusion, the pathogenic bacteria used in this study did not affect the pH and aW of the Camembert cheese samples.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".