Contamination ofSalmonella Schwarzengrund cells in chicken meat from traditional marketplaces in Taiwan and comparison of their antibiograms with those of the human isolates
Bibliographic record
Abstract
Salmonella Schwarzengrund is one of the infective Salmonella serotypes for humans and food animals, such as poultry and swine. Because consumption of foods containing salmonellae due to cross contamination or inadequate cooking may lead to human salmonellosis, in this report, the prevalence of Salmonella Schwarzengrund contamination in chicken meat samples purchased from different traditional marketplaces in Taiwan between 2000 and 2006 was investigated. In addition, 228 Salmonella Schwarzengrund strains isolated from these chicken meat samples and 30 human isolates obtained between 2004 and 2006 were compared for their antimicrobial susceptibility. Results showed that the prevalence of Salmonella Schwarzengrund contamination in raw chicken meat samples was 30.5%. Of all of the Salmonella isolates from chicken meat, Salmonella Schwarzengrund accounted for 39.3%. On the other hand, of the total Salmonella strains isolates from humans between 2004 and 2006, Salmonella Schwarzengrund accounted for 2.8%. All these chicken meat isolates and human isolates were multidrug-resistant and demonstrated high resistance to ampicillin, gentamicin, kanamycin, streptomycin, tetracycline, nalidixic acid, trimethoprim-sulfamethoxazole, and chloramphenicol. For gentamicin and kanamycin, however, the resistance gradually declined. The antibiogram study may indicate the abuse of some antibiotics for both humans and chickens. Also, transmission of Salmonella Schwarzengrund strains between humans and food of animal origin is possible.
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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 | 0.000 | 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".