LC-MS/MS method validation for determination of selected neonicotinoids in groundwater for the purpose of a column experiment
Bibliographic record
Abstract
The work was carried out to develop and validate a method based on liquid chromatography tandem mass spectrometry (LC-MS/MS) for the simultaneous detection and quantification of five neonicotinoid insecticides: acetamiprid, clothianidin, imidacloprid, thiacloprid and thiamethoxam in groundwater samples for the purpose of a further column experiment. This experiment will be used to analyze breakthrough curves of neonicotinoids under a saturated water flow to set transport parameters, where the reliability of the results of chemical analysis plays an important role. The validation was performed in a concentration range from 0.09 µg L−1 to 100 µg L−1 using an Infinity 1290 (Agilent, USA) chromatograph coupled with a QTrap 5500 mass spectrometer (Sciex, Canada). The calibration curves were obtained on the basis of the results of six standard solution analyses. Linearity was not lower than 0.998. The limit of detection was set at the lowest concentration which can be determined with an acceptable accuracy and precision. All pesticides had recoveries in the range 85–109% with relative standard deviation values less than 8.1%. The estimated measurement uncertainty did not exceed 30%, so the LC-MS/MS method fits for the intended purpose.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".