The determination of dimethyl sulfoxide in natural waters using electrochemical reduction
Bibliographic record
Abstract
Abstract A highly specific electrochemical reduction method has been developed that enables the trace level measurement of dimethyl sulfoxide (DMSO) concentration in natural waters. Following the sparging of native dimethyl sulfide (DMS) from the sample, DMSO is reduced to DMS using a novel electrochemical workflow that relies upon CuSO 4 as a redox mediator. The DMS produced through DMSO reduction is collected, concentrated, and detected using a previously described Purge & Trap‐Atmospheric Pressure Chemical Ionization‐Tandem Mass Spectrometry (P&T‐APCI‐MS/MS) analytical workflow. The method provides a 0.5 pM detection limit for the analysis of DMSO in 10 mL sample volumes, with a demonstrated method precision of 5.4% for the analysis of consecutive 10 nM aqueous standards. The method selectivity for DMSO was evaluated using a range of commonly observed marine organosulfur compounds, none of which were found to interfere with the analysis at a reduction potential of 4 V. Method intercomparison confirmed that the electrochemical reduction provides results that are equivalent (at the 95% confidence level) to an established TiCl 3 reduction protocol for the analysis of both freshwater and seawater samples. Relative to established methods of DMSO reduction, the electrochemical method provides excellent selectivity and reproducibility, and offers the potential for automated, high‐throughput analysis. In addition, the new electrochemical method does not require expensive, difficult to procure enzymes or hazardous, corrosive chemical reagents. Depth profile measurements of DMSO, DMS, and dimethylsulfoniopropionate (DMSP) for unfiltered seawater samples collected in Saanich Inlet, a coastal fjord in British Columbia, demonstrate the effectiveness of the DMSO reduction method in an oceanographic context.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".