Process Mapping the Prevalence of <i>Salmonella</i> Contamination on Pork Carcass from Slaughter to Chilling: A Systematic Review Approach
Bibliographic record
Abstract
A systematic review was conducted to identify and summarize primary research studies that describe the prevalence of Salmonella spp. in pork from slaughter to cooler in the member states of the European Union (EU), Australia, Canada, Hong Kong, Japan, Korea, Mexico, New Zealand, Taiwan, and United States (i.e., a process map). Relevant studies documented Salmonella spp. prevalence at more than one processing point using the same cohort of pigs or the same production line for the post-cooler component. Literature searches retrieved 6811 citations. Sixteen publications, describing 44 studies, evaluated the presence of Salmonella on pork carcasses. The carcass sampling points evaluated were as follows: stun, bleed, kill, scald, dehair, singe, polish, bung removal, evisceration, split, stamp, final wash, immediately after chill, and 18-48 h after chilling. Seventy-eight comparisons of Salmonella spp. prevalence between points along the processing line were reported. The median prevalence of Salmonella spp.-positive carcasses evaluated in the cooler was 0%. The median prevalence of Salmonella spp. after bleeding was 32%. Fifty-nine of the 78 point-to-point comparisons were associated with either no change or a decrease in Salmonella prevalence as the carcass moved closer to the cooler. Nineteen point-to-point changes showed an increase in Salmonella prevalence as the carcass moved toward the cooler; of these, six reported a greater than 10% increase in Salmonella prevalence. The majority of increases were associated with post-evisceration and splitting. These findings suggest that the processing procedures in place generally result in decreased prevalence of Salmonella spp. as the carcasses move toward the cooler.
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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 | 0.017 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.036 | 0.029 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".