Comparison of calibration strategies for accurate quantitation by isotope dilution mass spectrometry: a case study of ochratoxin A in flour
Bibliographic record
Abstract
Abstract Analysis of low-level organic contaminants in complex matrices is essential for monitoring global food safety. However, balancing sample throughput with complex experimental designs and/or sample clean-up to best reduce matrix effects is a constant challenge. Multiple strategies exist to mitigate these effects, with internal standard-based methods such as isotope dilution mass spectrometry (IDMS) being the most advantageous. Here, multiple internal calibration strategies were investigated for the quantification of ochratoxin A (OTA) in wheat samples by liquid chromatography-mass spectrometry (LC-MS). Internal standard-based quantitation methods such as single (ID 1 MS), double (ID 2 MS), and quintuple (ID 5 MS) isotope dilution mass spectrometry, as well as external standard calibration, were explored and compared. A certified reference material (CRM) of OTA in flour, MYCO-1, was used to evaluate the accuracy of each method. External calibration generated results 18–38% lower than the certified value for MYCO-1, largely due to matrix suppression effects. Concurrently, consistently lower OTA mass fractions were obtained for the wheat samples upon quantitation by external calibration as opposed to ID 1 MS, ID 2 MS, and ID 5 MS. All isotope dilution methods produced results that fell within the expected range for MYCO-1 (3.17–4.93 µg/kg), validating their accuracy. However, an average 6% decrease in the OTA mass fraction was observed from results obtained by ID 1 MS compared to those by ID 2 MS and ID 5 MS. Upon scrutiny, these differences were attributed to an isotopic enrichment bias in the isotopically labelled internal standard [ 13 C 6 ]-OTA that was used for ID 1 MS, the OTAL-1 CRM. The advantages and limitations of each isotopic method are illustrated.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".