Determination of Methylated Arsenic-Sulfur Compounds in Groundwater
Bibliographic record
Abstract
Arsenic speciation was determined by anion-exchange chromatography-inductively coupled plasma-mass spectrometry (AEC-ICP-MS) in groundwater samples collected from an aquifer impacted by methylated As pesticides. Besides the four expected arsenic species AsO3(3-), As4(3-), (CH3)AsO3(2-) and (CH3)2AsO2-, up to nine other arsenic species were encountered, which constituted a major fraction of the total arsenic concentration in most samples. We then synthesized the thio-derivatives of (CH3)AsO3(2-) and (CH3)2AsO2-, and characterized the formed products by electrospray-tandem mass spectrometry (ES-MS-MS). The presence of (CH3)AsO2S2-, (CH3)AsOS2(2-), (CH3)2AsOS- and (CH3)2AsS2-, was confirmed in the groundwater by retention time matching plus ES-MS-MS in collected AEC fraction, and the presence of the trivalent methylated arsenic species (CH3)AsO2(2-) was suggested based on retention time matching only. These arsenic species have not been observed in ambient waters before, and are likely to occur in many environments containing methylated arsenic species and reduced sulfur compounds. They can persist in some of these particular samples for periods of up to six months without preservation, but tend to convert into the corresponding pentavalent oxy-species. Acidification with HCI shifted speciation equilibria rapidly, and is thus unsuitable for stabilizing samples containing these novel arsenic species; cryofreezing or no sample preservation avoided this artifact.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".