Release of arsenic and molybdenum by reductive dissolution of iron oxides in a soil with enriched levels of native arsenic
Bibliographic record
Abstract
This study examined the release of arsenic (As), molybdenum (Mo), and iron (Fe) into the aqueous phase during reductive dissolution of iron oxides in an amended acid sulfate soil naturally enriched in arsenic. These acid sulfate soils occur worldwide and have a significant distribution in parts of Alberta and British Columbia. Reactions were studied in incubation vessels under controlled laboratory conditions. Soils were driven anaerobic by stimulation of indigenous bacteria using a glucose addition and then periodically analyzed for redox potential (Eh), pH, electrical conductivity, and aqueous concentrations of Fe, As, Mo, and other chemical species. Dissolution of iron oxides was pronounced when Eh values dropped to below +100 mV. With dissolution, concentrations of Fe, As, and Mo increased in the solution phase. Aqueous As concentrations increased from 0.87 to 119 μμg L1 during a reduction period of 48 d. Molybdate (MoO42), an oxyanion similar to arsenate, also closely followed the release of Fe and As into solution during the incubation. The results indicate both As and Mo behave similarly in response to the dissolution of soil iron oxides under reducing conditions and that their aqueous phase concentrations are largely controlled by dissolution and desorption from the iron oxide host. Key words: acid sulfate soil, arsenic, molybdenum, iron, redox potential, desorption.
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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".