Salmonella Prevalence is Low in Deep Tissue Lymph Nodes of Hog Carcasses from a Pork Processing Plant in Alberta, Canada
Bibliographic record
Abstract
Deep tissue lymph nodes (DTLNs) could be an important source of Salmonella in pork because carcass decontamination strategies have no effect on Salmonella cells that are deeply embedded and protected. The objective of this study was to determine the prevalence, concentration, and antimicrobial resistance of Salmonella in DTLNs in chilled hog carcasses as well as in ground pork. A total of 400 DTLNs were collected over a 10-month period from a commercial pork processing plant. Salmonella was detected in 2 (0.5%) of 400 DTLNs; Salmonella Uganda was detected in a DTLN from the belly and Salmonella Bovismorbificans in one DTLN from the shoulder. Salmonella Uganda was also detected in one ground pork sample. The three Salmonella isolates were susceptible to all antimicrobials tested, and no clinically significant antimicrobial resistance genes were detected in these genomes after sequencing. The prevalence of Salmonella in DTLNs in pork tissues intended for human consumption is very low and could be a minor source of contamination in the production of ground pork. These findings are important for the pork industry to assess the risks and benefits of removing DTLNs from pork cuts and trimmings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".