Evaluation of 3M Molecular Detection Assay (MDA) 2–Listeria for the Detection of Listeria Species in Select Foods and Environmental Surfaces: Collaborative Study, First Action 2016.07
Bibliographic record
Abstract
3M Molecular Detection Assay (MDA) 2-Listeria uses loop-mediated isothermal amplification and bioluminescence detection to rapidly detect Listeria species in a broad range of food types and environmental surfaces. Using an unpaired study design, MDA 2-Listeria was compared with the U.S. Department of Agriculture, Food Safety and Inspection Service's Microbiology Laboratory Guidebook Chapter 8.09 "Isolation and identification of Listeria monocytogenes from red meat, poultry and egg products, and environmental samples" reference method for the detection of Listeria in deli turkey and raw chicken breast fillet. Technicians from 13 laboratories located within the continental United States and Canada participated in the collaborative study. Each matrix was evaluated at three levels of contamination: uninoculated control (0 CFU/test portion), low inoculum (0.2-2 CFU/test portion), and high inoculum (2-5 CFU/test portion). Statistical analysis was conducted according to the probability of detection (POD) statistical model. Results obtained for the low-inoculum-level test portions produced a difference between two laboratory POD values (dLPOD) with 95% confidence intervals of 0.04 (-0.08, 0.17) for deli turkey, indicating the difference between the methods was not statistically significant at the P = 0.05. For raw chicken breast fillet, a dLPOD value with 95% confidence interval of 0.16 (0.04, 0.28) indicated a statistically significant difference between the two methods, with an observed higher proportion of positive results by the candidate method than the reference method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".