Determination of triglycidyl isocyanurate from air samples by ultra‐performance liquid chromatography coupled with coordination ion spray mass spectrometry
Bibliographic record
Abstract
RATIONALE: Ultra-performance liquid chromatography (UPLC) coupled with coordination ion spray tandem mass spectrometry was used for the analysis of air samples containing triglycidyl isocyanurate. The method is not affected by any chromatographic interference and the filter extract is compatible with the UPLC system, as opposed to approaches using high-performance liquid chromatography coupled with ultraviolet detection and gas chromatography coupled with mass spectrometry. METHODS: Accu-cap™ filters that had sampled triglycidyl isocyanurate were extracted using a mixture of acetonitrile/acetone (95/5) diluted with 3 volumes of water and were then analyzed. The mass spectrometry method uses sodium as the alkali adduct complexing with the triglycidyl isocyanurate in positive mode, and this complex is then analyzed using the survivor mode where the same ion is monitored in the first and third quadrupoles of a triple quadrupole mass spectrometer. RESULTS: The method has a limit of detection and limit of quantitation of 50 and 170 ng/filter, respectively. The dynamic range was between 480 and 24,000 ng/sample, which is equivalent to 2 µg/m(3) and 100 µg/m(3) based on a sampling volume of 240 L. The intra- and inter-day precisions were both <4% and the overall accuracy was 97 ± 3%. The method was tested with personal breathing zone random samples collected from workers using triglycidyl isocyanurate in their tasks, and all the random samples were easily quantified. CONCLUSIONS: A new method by UPLC coupled with coordination ion spray tandem mass spectrometry using sodium as the alkali adduct is now available for industrial hygienists who want to evaluate exposures of workers to triglycidyl isocyanurate in workplaces.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".