Method Extension Study to Validate Applicability of AOAC Official Method 996.14 Assurance® Polyclonal Enzyme Immunoassay for Detection of Listeria monocytogenes and Related Listeria spp. from Environmental Surfaces: Collaborative Study
Bibliographic record
Abstract
Test portions from 3 environmental surface types, representative of typical surfaces found in a food production facility, were analyzed by the Assurance Listeria Polyclonal Enzyme Immunoassay (EIA) and the U.S. Department of Agriculture/Food Safety and Inspection Service (USDA/FSIS) culture method for Listeria monocytogenes and related Listeria species. In all cases, naturally contaminated environmental test samples were collected from an actual food production facility by sponge or swab. Test samples from concrete surfaces were collected by both swab and sponge; sponge test samples were collected from rubber surfaces, and swabs were used to sample steel surfaces. Test portions from each surface type were simultaneously analyzed by both methods. A total of 23 collaborators, representing government agencies, as well as private industry in both the United States and Canada, participated in the study. During this study, a total of 550 test portions and controls was analyzed and confirmed, of which 207 were positive and 336 were negative by both methods. Six test portions were positive by culture, but negative by the EIA. Three test portions were negative by culture, but positive by the EIA. Two test portions were negative by EIA and by culture, but confirmed positive when EIA enrichment broths were subcultured to selective agars. The data reported here indicate that the Assurance Listeria EIA method and the USDA/FSIS culture method are statistically equivalent for detection of L. monocytogenes and related Listeria species from environmental surfaces taken by sponges or swabs.
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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 | 0.055 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".