Characterization of Salmonella enterica serovar Typhimurium isolates associated with septicaemia in swine
Bibliographic record
Abstract
In th1s study we characterized, usmg genotyping and phenotypmg methods, ISolates {n=33) from septicaemia outbreaks in swine herds as well as isolates {n=33) recovered from healthy ammals at slaughter.We determined the antimicrobial agents resistance profiles using 24 different an timicrobial agents by the d1sk d1ffus1on on agar method, the phage type, the plasmid profiles and the PFGE profiles usmg Xbal and Spel as restriction enzymes for each isolates.Resistance to as much as 10 antimicrobial agents was found in both categories of isolates.A greater number of PFGE genotypes was observed in isolates from septicaemia.Various phage types were 1dent1fied in both groups of isolates.Among the DT1 04 phage type, many genetic clusters were 1dent1fied Analysis of plasmid profiles indicated that septicemic strains possess higher molecular we1ght plasmids than asymptomatic 1solates.These results Indicated that strams associated w1th sept1caem1a belong to various genet1c lineages and suggest that VIrulence tra1ts are assoc1ated w1th plasmid profiles of stra1ns.Our results also suggest that the genetic d1vers1ty of Salmonella DT 104 m1ght be higher m North Amenca if we cons1der results of s1milar studies m Europe
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".