Remediation of DDT‐contaminated soil using optimized mixtures of surfactants and a mixing system
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
Abstract Soil contaminated with persistent pesticides, such as DDT, poses a serious risk to humans and to wildlife. A surfactant‐aided soil‐washing technique was studied as an alternative method for remediation of DDT‐contaminated soil. An ex situ soil washing method was investigated using nonionic and anionic surfactants due to the clayey structure of the contaminated soil. A mixture of 1 percent nonionic surfactant (Brij 35) and 1 percent anionic surfactant (SDBS) removed more than 50 percent of DDT from soil in a flow‐through system, whereas individual surfactants or other combinations of the surfactants had a lower removal efficiency. The soil‐washing technique was improved using a mixing system. The mixture of surfactants was optimized in the mixing system, and the combination of 2 percent Brij 35 and 0.1 percent SDBS was found to be optimum, removing 70 to 80 percent of DDT. Prewashing of the soil with tap water decreased the adsorption of surfactants to soil particles by 30 to 40 percent, and postwashing recovered 90 percent of the surfactants. © 2010 Wiley Periodicals, Inc.
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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 | 0.001 |
| 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 | 0.000 | 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