Quantitative determination of marine lipophilic toxins in mussels, oysters and cockles using liquid chromatography-mass spectrometry: inter-laboratory validation study
Bibliographic record
Abstract
Thirteen laboratories participated in an inter-laboratory study to evaluate the method performance characteristics of a liquid chromatography-tandem mass spectrometric method (LC-MS/MS) for marine lipophilic shellfish toxins. Method performance characteristics were evaluated for mussel (Mytilus edulis), oyster (Crassostrea gigas) and cockle (Cerastoderma edule) matrices. The specific toxin analogues tested included okadaic acid (OA), dinophysistoxins-1 and -2 (DTX1, -2), azaspiracids-1, -2 and -3 (AZA1, -2, -3), pectenotoxin-2 (PTX2), yessotoxin (YTX), and 45-OH-yessotoxin (45-OH-YTX). The instrumental technique was developed as an alternative to the still widely applied biological methods (mouse or rat bioassay). Validation was conducted according to the AOAC-harmonised protocol for the design, conduct and interpretation of method-performance studies. Eight different test materials were sent as blind duplicates to the participating laboratories. Twelve laboratories returned results that were accepted to be included in the statistical evaluation. The method precision was expressed as HORRATs. For the individual toxins (except for 45-OH-YTX) HORRATs were found to be ≤1.8 (median HORRAT=0.8) in all tested materials. The recoveries of OA-, AZA- and YTX-group toxins were within the range of 80-108% and PTX2 was within the range of 62-93%. Based on the acceptable values for precision and recovery, it was concluded that the method is suitable for official control purposes to quantitatively determine OA/DTXs, AZAs, YTXs and PTX2 in shellfish.
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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 | 0.023 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".