Specific Treatment Technologies for Removing Arsenic from Water
Bibliographic record
Abstract
Abstract Arsenic (As) is a highly toxic metalloid found in ground and surface water. Arsenic contamination in drinking water leads to harmful effects on human health. To eliminate arsenic from drinking water, several technologies such as coagulation, adsorption, ion exchange, filtration, membrane processes, etc., have been used. In this study, three technologies were evaluated for arsenic removal. Results from batch kinetic experiments showed that iron coated sand (IOCS‐2) can remove more than 90 % of As from synthetic water. Experiments were conducted with three different pH values (6, 7, and 8) and an initial As concentration of 260 μg/L. A new material, developed in this study, namely iron coated sponge (IOCSp), was found to have a high capacity in removing both As (V) and As (III). Each gram of IOCSp adsorbed about 160 μg of As within a 9‐hour contact period of IOCSp with As solution. Low pressure nanofiltration removed more than 94 % of As from an influent containing 440 μg/L As. The applied pressure was varied from 85 to 500 kPa.
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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 | 0.000 |
| 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 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".