Determination of Pesticides in Soy-Based Infant Formula Using Liquid Chromatography with Electrospray Ionization Tandem Mass Spectrometry
Bibliographic record
Abstract
A sensitive method using liquid chromatography with electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) was developed and validated to quantify and confirm 13 pesticides, including aldicarb sulfoxide, aldicarb sulfone, oxamyl, methomyl, formetanate, 3-hydroxycarbofuran, carbendazim, thiabendazole, aldicarb, propoxur, carbofuran, carbaryl, and methiocarb, in soy-based infant formula. Data acquisition under MS/MS was achieved by applying multiple reaction monitoring of 2 fragment ion transitions to provide a high degree of sensitivity and selectivity for both quantitation and confirmation. Different approaches to constructing calibration curves were compared and discussed to address issues of the extraction efficiency or recovery, and matrix effects. Matrix-matched standard calibration curves with the use of isoprocarb as an internal standard were finally used to achieve the best accuracy of the method. Under most circumstances, recoveries of 13 pesticides, spiked at 5.0, 25.0, and 45.0 microg/kg, were close to 100%. The method detection limits (signal-to-noise ratio > or =3:1; microg/kg) of 13 pesticides were 0.2 for thiabendazole and methiocarb, 0.6 for aldicarb, and 0.1 for the others.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".