Effect of Multiple Freeze-thaw Cycles on the Microflora of Quick-frozen Dumplings
Bibliographic record
Abstract
The effect of temperature fluctuations caused by repeated freeze-thaw cycles on the number and diversity of microorganisms in quick-frozen dumplings was investigated using polymerase chain reaction-denaturing gradient gel electrophoresis(PCR-DGGE) and traditional plate culture methods. The dumpling fillers were inoculated with Staphylococcus aureus to analyze the dynamic changes in S. aureus itself and its influence on the dumpling microflora. The results showed that the quantity and diversity of microorganisms in the dumplings increased significantly(p 0.05) with increasing freeze-thaw cycles. At the last cycle, S. aureus count in the inoculated dumplings increased from 3.49 to 5.07 log10 CFU/g, which reached the minimum count for Staphylococcal toxicity, of 105 CFU/g. PCR-DGGE showed that lactic acid bacteria, Pseudomonadales bacterium and Brochothrix thermosphacta were the dominant strains in the dumplings during the freeze-thaw cycles, while the counts of S. aureus increased and finally became the dominant strain. The results of PCR-DGGE and the traditional culture method were generally consistent.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".