DuPont BAX<sup>®</sup> System PCR Assay for Genus <i>Listeria</i> 24E
Bibliographic record
Abstract
The DuPontTM BAX® System PCR assay for Genus Listeria 24E using 24 LEB was assessed to detect Listeria spp. from food and stainless steel surfaces. The assay protocol used in these studies includes test kit lysis reagents that differ from those used in previous BAX System PCR assays (and are similar to those in the BAX System reverse-transcriptase PCR test kit for Listeria spp.) and a new proprietary enrichment medium optimized for use with this test kit. The genomic target for PCR in the Genus Listeria 24E assay is the same as that used in the previously-validated BAX System PCR assay for Genus Listeria (AOAC-RI Performance Tested MethodSM 030502), but the redesign of the test kit and new medium allow for faster target cell growth, a more quantitative lysis of enriched cells and a faster time to result. Five foods—liver paté, hot dogs, raw fermented sausage, sliced deli turkey, and sliced deli ham—and one environmental surface type, stainless steel, were simultaneously analyzed with the BAX System Q7 instrument and the Health Canada MFHPB-30 method for detecting Listeria spp. One food type, hot dogs, was artificially inoculated with L. innocua and Enterococcus faecalis. The environmental surfaces were co-inoculated with both L. monocytogenes and E. faecalis; all the other matrixes were inoculated with a single strain of L. monocytogenes. No significant differences were found in method performance when the test method was compared with the reference method.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.014 |
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".