Determination of <i>trans</i>,<i>trans</i>‐muconic acid in workers' urine through ultra‐performance liquid chromatography coupled to tandem mass spectrometry
Why this work is in the frame
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Bibliographic record
Abstract
A novel method for the biological monitoring of benzene-exposed workers has been developed through ultra-performance liquid chromatography coupled to tandem mass spectrometry. The method uses trans,trans-muconic acid in urine as the benzene-exposure biomarker. The method was developed using a triple quadrupole mass spectrometer with enough sensitivity to facilitate diluting and injecting the urine samples directly, rather than performing a solid-phase extraction procedure as is common in the available protocols. Moreover, compared with a conventional high-pressure liquid chromatography system, the separation power provided by the ultra-performance liquid chromatography system allows a 10-fold reduction in run time. The method was adjusted to a dynamic range of between 198.9 and 4916.7 µg/L to cover the biological exposure index of trans,trans-muconic acid in urine. Also, the method demonstrated intra-day and inter-day precision at 98%, and accuracy within an acceptable range of 101 ± 8%. The method has been used to quantify various types of urine samples, such as workers' urine and inter-laboratory proficiency tests. Depending on the sample, the quantified levels ranged from less than the limit of quantitation to 3836.7 µg/L. No levels exceeding the calibration range were detected in the urine of workers, and the reported concentrations in urine for the proficiency tests were, as expected, based on known values. Moreover, the new method using sample dilution and faster chromatographic run was more effective, facilitating fast communication of results, as needed, to decision-makers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it