Thioarsenates in Geothermal Waters of Yellowstone National Park: Determination, Preservation, and Geochemical Importance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mono-, di-, tri-, and tetrathioarsenate, as well as methylated arsenic oxy- and thioanions, were determined besides arsenite and arsenate in geothermal waters of Yellowstone National Park using anion-exchange chromatography inductively coupled plasma mass spectrometry. Retention time match with synthetic standards, measured S:As ratios, and molecular electrospray mass spectra support the identification. Acidification was unsuitable for arsenic species preservation in sulfidic waters, with HCI addition causing loss of total dissolved arsenic, presumably by precipitation of arsenic-sulfides. Flash-freezing is preferred for the preservation of arsenic species for several weeks. After thawing, samples must be analyzed immediately. Thioarsenates occurred over a pH range of 2.1 to 9.3 in the geothermal waters. They clearly predominated under alkaline conditions (up to 83% of total arsenic), but monothioarsenate also was detected in acidic waters (up to 34%). Kinetic studies along a drainage channel showed the importance of thioarsenates for the fate of arsenic discharged from the sulfidic hot spring. The observed arsenic speciation changes suggest three separate reactions: the transformation of trithioarsenate to arsenite (major initial reaction), the stepwise ligand exchange from tri- via di- and monothioarsenate to arsenate (minor reaction), and the oxidation of arsenite to arsenate, which only becomes quantitatively important after thioarsenates have disappeared.
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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 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it