Solid phase microextraction gas chromatography-glow discharge-optical emission detection for tin and lead speciation
Bibliographic record
Abstract
A modified interface between a gas chromatograph (GC) and a hollow cathode (HC) radiofrequency (rf) glow discharge (GD) with detection by optical emission spectrometry (OES) has been investigated for elemental speciation studies. Solid phase microextraction (SPME), used for extraction and preconcentration of organic compounds, is here used for the introduction of the metal species under investigation into the injector of the GC, after preconcentration of metal species ethylated “in situ” with sodium tetraethylborate. Tin [monobutyltin (MBT), dibutyltin (DBT) and tributyltin (TBT)] and lead species [trimethyllead (TML) and triethyllead (TEL)] were used as models and separated using a capillary column. Detection by rf-(HC)GD-OES was accomplished at 283.9 nm for tin and 283.3 nm for lead. After optimization of the parameters affecting the rf-(HC)GD signals (pressure, radiofrequency power and He flow rate used as plasma gas) and also the parameters affecting the SPME technique (adsorption time, desorption time, injector temperature and position of the fiber into the injector of the GC), the analytical characteristics were calculated. Good detection limits for the tin and lead species under study (0.021 µg L−1 for MBT, 0.026 µg L−1 for DBT, 0.075 µg L−1 for TBT, 0.03 µg L−1 for TEL and 0.15 µg L−1 for TML) were achieved. Finally, the accuracy of the proposed speciation methodology was tested by analysing a certified reference material (sediment PACS-2) from the National Research Council of Canada.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".