Application of ISO 16140-3:2021 – Key Concepts and Examples of Verification of Alternative Methods
Bibliographic record
Abstract
Verification of the methods routinely used in the laboratory is a requirement for laboratories accredited to the International Organization for Standardization (ISO) standard: ISO/IEC 17025:2017 General requirements for the competence of testing and calibration laboratories.1 A method verification protocol is not specified within the ISO 17025:2017 standard, and until now, laboratories have been required to conduct their verification studies based on protocols either developed in-house, or using locally recognized protocols, such as: NATA Technical Note 17,2 Health Canada Compendium of Methods,3 etc. The publication of ISO 16140-3:2021 Microbiology of the food chain — Method validation — Part 3: Protocol for the verification of reference methods and validated alternative methods in a single laboratory4 now provides an internationally developed and recognized protocol that may be used to fulfill this requirement. An orientation to some of the key concepts within the ISO 16140-3:2021 standard is presented and demonstrated using examples of verification of both a qualitative method (Neogen® Molecular Detection Assay 2 – Salmonella (MDA2 SAL) and a quantitative method Neogen® Petrifilm® Enterobacteriaceae Count Plate (Petrifilm EB Plate).
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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 | 0.051 | 0.070 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.016 |
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".