Evaluation of the Thermo Scientific™ SureTect™ Listeria species Assay
Bibliographic record
Abstract
The Thermo Scientific SureTect Listeria species Assay is a new real-time PCR assay for the detection of all species of Listeria in food and environmental samples. This validation study was conducted using the AOAC Research Institute (RI) Performance Tested Methods program to validate the SureTect Listeria species Assay in comparison to the reference method detailed in International Organization for Standardization 11290-1:1996 including amendment 1:2004 in a variety of foods plus plastic and stainless steel. The food matrixes validated were smoked salmon, processed cheese, fresh bagged spinach, cantaloupe, cooked prawns, cooked sliced turkey meat, cooked sliced ham, salami, pork frankfurters, and raw ground beef. All matrixes were tested by Thermo Fisher Scientific, Microbiology Division, Basingstoke, UK. In addition, three matrixes (pork frankfurters, fresh bagged spinach, and stainless steel surface samples) were analyzed independently as part of the AOAC-RI-controlled independent laboratory study by the University ofGuelph, Canada. Using probability of detection statistical analysis, a significant difference in favour of the SureTect assay was demonstrated between the SureTect and reference method for high level spiked samples of pork frankfurters, smoked salmon, cooked prawns, stainless steel, and low-spiked samples of salami. For all other matrixes, no significant difference was seen between the two methods during the study. Inclusivity testing was conducted with 68 different isolates of Listeria species, all of which were detected by the SureTect Listeria species Assay. None of the 33 exclusivity isolates were detected by the SureTect Listeria species Assay. Ruggedness testing was conducted to evaluate the performance of the assay with specific method deviations outside of the recommended parameters open to variation, which demonstrated that the assay gave reliable performance. Accelerated stability testing was additionally conducted, validating the assay shelf life.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".