Improvement of Measurement Precision of SPME-GC/MS Determination of Tributyltin Using Isotope Dilution Calibration
Bibliographic record
Abstract
A unique approach was developed to improve the precision of quantification of tributyltin (TBT) in sedimentsby solid phase microextraction (SPME) using isotope dilution GC/MS. The precision of the analytical technique was initially evaluated using standard calibration solutions. In selective ion monitoring (SIM) mode, the relative standard deviation (RSD) obtained for TBT based on peak area response was 18% (n = 11). When an internal standard, tripropyltin (TPrT), was used, the RSD decreased to 12%. A significant improvement in the precision using SPME was noted when a 117Sn-enriched TBT spike was employed; the RSD decreased 4-fold to 3%. Detection limits of 0.2 and 20 ng(Sn) L(-1) were achieved with SPME sampling and liquid-liquid extraction, respectively. Six analyses were performed for determination of TBT in PACS-2 sediment Certified Reference Material using both standard additions and isotope dilution procedures. For the latter, a 117Sn-enriched TBT spike was used. A concentration of 0.88 +/- 0.03 microg g(-1) (RSD 3.4%) obtained using standard additions was in good agreement with the certified value of 0.98 +/- 0.13 microg g(-1) as tin. Concentrations found using isotope dilution were 0.895 +/- 0.015 microg g(-1) (RSD 1.73%) as tin and 0.874 +/- 0.014 microg g(-1) (RSD 1.66%) as tin using a liquid-liquid extraction and SPME sampling, respectively. A 2-fold improvement in the precision of TBT concentration measurement using isotope dilution was clearly achieved, demonstrating its superiority in providing more accurate and precise results as compared to the method of standard additions. The isotope dilution technique eliminated the problem of poor reproducibility, which typically plagues SPME.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".