Enhanced Pesticide Screening in Wines and Juices by Column-Switching Liquid Chromatography-Tandem Mass Spectrometry Using Multiple Activation Methods
Bibliographic record
Abstract
A commercial QqTOF platform (ZenoTOF 7600 system) was modified to enable three fragmentation modes, collision induced dissociation (CID), electron activated dissociation (EAD) and ultraviolet photodissociation (UVPD) at 266 nm. 168 pesticides, which showed fragmentation in CID provides also EAD spectra. In the case of UVPD, 158 compounds fragmented under 266 nm photon irradiation. The performance of the novel platform was evaluated using data independent CID SWATH acquisition for the general screening and schedule multiple product ion acquisition with CID/EAD/UVPD for confirmatory analysis of pesticides in juice, white and red wines samples. A column-switching LC method with online dilution was developed allowing for injection of large volumes (80 μL) into the system. The approach enabled the detection and concentration estimation of approximately thirty pesticides in juices and wines, including insecticides, neonicotinoids and fungicides. Pesticide LODs were found to be in the pg/ml to ng/ml range for MS1 and MS2 acquisitions.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".