Method Modification of the Thermo Scientific SureTect Listeria monocytogenes Assay for Raw Meat, Dairy, Produce, and Seafood
Bibliographic record
Abstract
The Thermo Scientific™ SureTect™ Listeria monocytogenes assay is a real-time PCR assay for the detection of Listeria monocytogenes in food and environmental samples, which was certified during 2013 by the AOAC Research Institute (RI) as Performance Tested Method(SM) (PTM) 061302 for a representative range of key food matrixes and production surfaces. This report details the method modification study, which was conducted during 2014, using the AOAC-RI PTM program to extend the validated matrix claims of the assay in comparison to the reference method detailed in International Organization for Standardization 11290-1:1996, including Amendment 1:2004, to gain certification for raw ground turkey, raw ground pork, pasteurized 2% milk, raw pork sausages, raw cod, pasteurized brie cheese, cooked sliced ham, and bagged lettuce. All matrixes were tested by Thermo Fisher Scientific, Microbiology Division, Basingstoke, UK. In addition, brie cheese, bagged lettuce, and raw cod were analyzed independently by the University of Guelph, Canada, during the AOAC-RI controlled independent laboratory study. Using probability of detection (POD) statistical analysis, a significant difference was demonstrated between the candidate and reference methods for the high spiking level with raw ground pork and brie cheese. For all other matrixes and the low spiked levels for raw ground pork and brie cheese, no significant difference by POD was seen between the two methods during the study.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".