SURVIVAL OF THREE <i>SALMONELLA</i> SEROTYPES ON BEEF TRIMMINGS DURING SIMULATED COMMERCIAL FREEZING AND FROZEN STORAGE
Bibliographic record
Abstract
ABSTRACT This study investigated the survival of three Salmonella serotypes (S. Brandenberg, S. Dublin and S. Typhimurium) on beef trimmings during simulated commercial freezing, frozen storage for 9 months and subsequent abusive slow thawing and refreezing conditions. This was achieved by plating samples monthly and after thawing and refreezing on nonselective Tryptic Soy Agar (TSA) and selective Xylose Lysine Desoxycholate Agar (XLD) and incubating both at 37C for 24 h to determine Salmonella counts, aerobic counts and the presence, if any, of sublethal injury of this pathogen. Two freezing temperatures (−18C or −35C) to simulate slow or rapid freezing respectively, and two inoculation levels (103 cfu g−1 or 105 cfu g−1) were used. Aerobic counts and counts of all the Salmonella serotypes did not change significantly (p > 0.05) during frozen storage or for any of the other treatments applied in this study. This finding was attributed to the insulating nature of the subcutaneous fat layer in this manufacturing cut. These results are important with respect to food safety associated with ground beef processing.
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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) | 0.000 | 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) | 0.001 | 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".