A real-time PCR regimen for testing environmental samples for <i>Salmonella enterica</i> subsp. <i>enterica</i> serovars of concern to the poultry industry, with special focus on <i>Salmonella</i> Enteritidis
Bibliographic record
Abstract
A real-time PCR (qPCR) regimen, using up to six genetic targets, was developed to rapidly detect Salmonella and in particular identify Salmonella Enteritidis. The test regimen was first evaluated using a reference culture collection of Salmonella to confirm the appropriateness of the selected targets, which included up to three genetic markers for discrimination of Salmonella Enteritidis from other Salmonella serovars commonly found in poultry facilities. The qPCR procedure was then compared with culture methods used to detect Salmonella using a collection of enrichment broths previously generated from 239 environmental samples collected from a large number of hatchery facilities across Canada over several years. The qPCR regimen facilitated specific detection of Salmonella Enteritidis, and on a sample basis, it showed excellent agreement with the culture methods. Moreover, in many cases, qPCR detected Salmonella earlier in the culture process than did the culture method. Application of this method will significantly shorten test times and allow more timely identification of infected poultry premises, thereby improving present programmes aimed at controlling Salmonella Enteritidis at the environmental source.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".