New Method and Detection of High Concentrations of Monomethylarsonous Acid Detected in Contaminated Groundwater
Bibliographic record
Abstract
Monomethylarsonous acid (MMAIII) was detected in groundwater from a former herbicide production plant in the USA. The site has total arsenic concentrations up to thousands of mg/L, representing one of the most severe cases of arsenic contamination ever reported. Structure-specific detection of MMAIII, along with arsenite (AsIII), arsenate (AsV), monomethylarsonic acid (MMAV), and dimethylarsinic acid (DMAV), was achieved using liquid chromatography separation with electrospray ionization tandem mass spectrometry detection (HPLC-ESI-MS/MS). To enable the electrospray of MMAIII and AsIII, dimercaptosuccinic acid (DMSA) was used to derivatize these trivalent arsenicals online, so that their complexes with DMSA could be detected using negative ionization ESI-MS/MS. The presence of MMAIII was verified using high resolution mass spectrometry to measure accurate mass, tandem mass spectrometry to monitor fragmentation, and three different separation techniques to resolve arsenic species. The measured accurate mass of the suspected MMAIII compound in a groundwater sample was 122.9607+/-0.0003 amu, which was in good agreement with the theoretical value and that of the MMAIII standard. Simultaneous monitoring of AsO+ at m/z 91 and SO+ at m/z 48 using HPLC-ICPMS operating in dynamic reaction cell mode ruled out possible confounding from any sulfur-containing arsenic compound. The concentrations of MMAIII found in the groundwater samples from a contaminated site were as high as 3.9-274 mg/L, the highest ever observed in the environment.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".