Estimation of the Diagnostic Accuracy of the<i>invA</i>‐gene‐based PCR Technique and a Bacteriological Culture for the Detection of<i>Salmonella</i>spp. in Caecal Content from Slaughtered Pigs using Bayesian Analysis
Bibliographic record
Abstract
The goal of this study was to estimate the accuracy of the invA-gene-based polymerase chain reaction (PCR) and a culture technique based on pre-enrichment with buffered peptone water, three selective enrichment media (selenite, tetrathionate and Rappaport-Vassiliadis broths) and four selective, solid media (Xylose-Lysine-Tergitol-4, Salmonella/Shigella, Hekton-Enteric and MacConkey), for the detection of Salmonella organisms from caecal samples from slaughter pigs. For this purpose a latent-class (Bayesian) approach was used. Two hundred and three slaughtered pigs were used after grouping them into two groups of 96 and 107 animals. Sensitivity (Se) was estimated to be 56% (95% probability interval 40, 76) for culture and 91% (81, 97) for PCR. The specificity (Sp) of the PCR was 88% (80, 95) while the Sp of the culture had been considered 100% in the statistical analysis as all culture-positive samples were confirmed by serotyping. PCR Se was not affected by the Salmonella serotypes present in the samples analysed. Accordingly, a minimum of 25.5% of the pigs was estimated to harbour Salmonella organisms in their faeces. It was concluded that bacteriology on caecal samples alone was a poor diagnostic method, and that the PCR method could be considered a cost-effective alternative to culture in Salmonella monitoring programmes. However, given the moderate Sp of this molecular technique, PCR-positive samples should be further confirmed through bacteriology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".