Performance Validation of the IEH Laboratories Multiplex PCR <i>Listeria</i> Detection System for Environmental Samples in Comparison to Health Canada Reference Method (MFHPB-30) for <i>Listeria</i> Detection
Bibliographic record
Abstract
BACKGROUND: Laboratory detection methods are commonly tested against gold standards and corresponding reference methods to confirm their suitability and efficiency. OBJECTIVE: The IEH Listeria Test System (multiplex PCR) was tested against Health Canada's reference method (MFHPB-30) for the simultaneous detection of Listeria spp. and Listeria monocytogenes on three different surfaces: plastic (PL), sealed concrete (SC), and stainless steel (SS). METHODS: The R2 medium was used for pre-enrichment of the samples at 35°C for 24 h, followed by the IEH Listeria multiplex PCR. Each individual surface coupon (PL, SC, and SS) was inoculated with either Listeria innocua, L. monocytogenes, or L. welshimeri along with two non-target microorganisms of concern and subjected to candidate (IEH Listeria multiplex PCR) and reference method (MFHPB-30) testing in an unpaired manner, including culture confirmation for the IEH method. RESULTS: The candidate method demonstrated 0% false negative, 0% false positive, 100% sensitivity, and 100% specificity after only 24 h enrichment followed by multiplex PCR. CONCLUSIONS: Evaluating the differences between the candidate and reference method detection probabilities across all three surface types revealed that the candidate method was equivalent to MFHPB-30, while requiring significantly less time for detection. HIGHLIGHTS: IEH Listeria system performed equivalently to the reference method, without being affected by the surface type and while decreasing the detection time to a total of less than 28 hours.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".