Competition by aquifer materials in a bimetallic nanoparticle/persulfate system for the treatment of trichloroethylene
Bibliographic record
Abstract
It has been suggested in the literature that aquifer materials can compete with the target organic compounds in an activated peroxygen system. In this study, we employed a rapid treatment method using persulfate activated with bimetallic nanoparticles to investigate the competition between aquifer materials and the dissolved phase of a target organic compound. The concentration of dissolved trichloroethylene (TCE) remaining after using the activated persulfate system was two- to three-fold higher in a soil slurry batch system than in an aqueous batch system. For all five aquifer materials investigated, an increase in the mass of the aquifer solids significantly decreased the degradation of TCE. A linear relationship was observed between the mass of aquifer materials and the initial TCE degradation rate, suggesting that the organic carbon and/or aquifer material constituents (e.g., carbonates and bicarbonates) compete with the oxidation of TCE.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".