An investigation into distribution of serotypes and antimicrobial resistance patterns of Streptococcus suis isolates from clinical cases and healthy carrier pigs
Bibliographic record
Abstract
The distribution of Streptococcus suis serotypes and antimicrobial resistance patterns in clinical cases and healthy carrier pigs was investigated. Isolates were confirmed as S. suis by various biochemical techniques and serotyped using multiplex PCR amplification. Antimicrobial susceptibility testing was performed using the disk diffusion method. Recovery of S. suis was more likely in samples from suckling and nursery piglets than from sows and finishers (P <0.001), and more commonly recovered from healthy pigs as opposed to sick pigs (P <0.01). Samples from pigs in a continuous flow system were more likely to be found to be S. suis positive than those from pigs in an all-in/all-out system (P <0.01). Twenty-two different serotypes were identified, with types 5, 9, and 31 being the most common types isolated. Most isolates (94.5%) were resistant to at least one antimicrobial agent. A low prevalence of resistance was seen against ampicillin, ceftiofur, and florfenicol (<1.0%), while a high prevalence of resistance against tetracycline (84.2%), tiamulin (65.2%), and spectinomycin (40.4%) and an intermediate level of resistance to trimethoprim/sulfa (13.2%) was identified.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".