3M™ Tecra™ Listeria Visual Immunoassay: AOAC Official MethodsSM 995.22 and 2002.09
Bibliographic record
Abstract
A validation study of the 3M Tecra Listeria Visual Immunoassay (VIA; 3M Food Safety, St. Paul, MN) was conducted at Q Laboratories, Inc., Cincinnati, OH. The 3M Tecra Listeria VIA method was compared to the Health Canada MFHPB-30 reference method for the analysis of five ready-to-eat (RTE) meats: deli turkey, hot dogs, liver pate, raw fermented sausage, and deli ham, and on a stainless steel environmental surface. Twenty replicates of each of the five food matrixes were analyzed at a low and a high inoculum level. The low-level test portions were inoculated with 0.2-2 CFU/25 g, and the high-level test portions with 2-5 CFU/25 g. In addition, 20 replicates of one environmental surface were analyzed at a low and a high inoculum level. The low-level sampling area was inoculated with 0.2-2 CFU/5 cm2, and the high-level area with 2-5 CFU/5 cm2. Five control replicates were also analyzed at 0 CFU/25 g (uninoculated) for the foods and at 0 CFU/5 cm2 for the environmental sampling area. There was no significant difference in the number of positives detected by the 3M Tecra Listeria VIA and the Health Canada MFHPB-30 reference method for four of the RTE meats and the stainless steel environmental surface analyzed in this study. For the raw, fermented sausage, there was a significant difference in the number of positives detected for the high inoculum level by the 3M Tecra Listeria VIA and the Health Canada MFHPB-30 reference method, with the 3M Tecra Listeria VIA method detecting more positives.
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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 | 0.016 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.029 |
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".