Iron-Coated Sponge as Effective Media to Remove Arsenic from Drinking Water
Bibliographic record
Abstract
Abstract Arsenic (As) contamination in drinking water is a serious problem in a number of countries in the world, especially in small communities and developing countries. Arsenic is related to many health diseases. Several technologies such as coagulation, adsorption, ion exchange and membrane processes, etc., are used in removing arsenic from water. In this study, a new material, namely iron-coated sponge (IOCSp), was developed and used to remove As, and it was found that IOCSp has a high capacity for removing both As(V) and As(III). Each gram of IOCSp adsorbed about 160 µg of As upon a 9-h contact of IOCSp with As solution. A dynamic filter column conducted showed that even a small quantity of IOCSp (8 g) could reduce As from 156 µg/L to a concentration of less than 50 µg/L while treating 75 L of groundwater contaminated with arsenic. Both the filtration rate and the size of the sponge had an effect on effluent quality, and the amount of water treated to the acceptable quality.
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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 | 0.005 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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; both teacher heads agree on what is shown here.
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".