Phosphate interference during in situ treatment for arsenic in groundwater
Bibliographic record
Abstract
Contamination of groundwater by arsenic is a problem in many areas of the world, particularly in West Bengal (India) and Bangladesh, where reducing conditions in groundwater are the cause. In situ treatment is a novel approach wherein, by introduction of dissolved oxygen (DO), advantages over other treatment methods can be achieved through simplicity, not using chemicals, and not requiring disposal of arsenic-rich wastes. A lab-scale test of in situ treatment by air sparging, using a solution with approximately 5.3 mg L(-1) ferrous iron and 200 μg L(-1) arsenate, showed removal of arsenate in the range of 59%. A significant obstacle exists, however, due to the interference of phosphate since phosphate competes for adsorption sites on oxidized iron precipitates. A lab-scale test including 0.5 mg L(-1) phosphate showed negligible removal of arsenate. In situ treatment by air sparging demonstrates considerable promise for removal of arsenic from groundwater where iron is present in considerable quantities and phosphates are low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 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".