Determination of Triphenylmethane Dyes and Their Metabolites in Salmon, Catfish, and Shrimp by LC-MS/MS Using AOAC First Action Method 2012.25: Collaborative Study
Bibliographic record
Abstract
A collaborative study was conducted to evaluate the AOAC First Action 2012.25 LC-MS/MS analytical method for the determination of residues of three triphenylmethane dyes (malachite green, crystal violet, and brilliant green) and their metabolites (leucomalachite green and leucocrystal violet) in seafood. Fourteen laboratories from the United States, Canada, and the European Union member states participated in the study including national and state regulatory laboratories, university and national research laboratories, and private analytical testing laboratories. A variety of LC-MS/MS instruments were used for the analysis. Each participating laboratory received blinded test samples in duplicate of salmon, catfish, and shrimp consisting of negative control matrix; matrix fortified with residues at 0.42, 0.90, and 1.75 μg/kg; and samples of incurred matrix. The analytical results from each participating laboratory were evaluated for both quantitative residue determination and qualitative identification of targeted analytes. Results from statistical analysis showed that this method provided excellent trueness (generally ≥90% recovery) and precision (RSDr generally ≤10%, HorRat<1). The Study Directors recommend Method 2012.25 for Final Action status.
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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 | 0.024 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".