The impact of permanganate on the ability of granular iron to degrade trichloroethene
Bibliographic record
Abstract
Abstract The primary goal of this study was to investigate the influence of permanganate (MnO 4 − ) on the performance of granular iron permeable reactive barriers. The degradation of trichloroethene (TCE) was measured initially and then over time as a MnO 4 − solution was passed through laboratory columns packed with granular iron. Concentration profiles for MnO 4 − , TCE, and degradation products (dichloroethene isomers and vinyl chloride), as well as pH, were observed. The pH increased sharply after passing MnO 4 − through the column, from ~8 to 11. MnO 4 − rapidly oxidized the granular iron and formed insoluble precipitates and oxide films or coatings on the granular iron surfaces. The precipitates did not accumulate in sufficient quantity to cause a measurable decline in hydraulic conductivity; however, the surface films formed as a consequence of the addition of MnO 4 − caused the iron to become nonreactive with respect to both MnO 4 − and 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) | 0.000 | 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) | 0.001 | 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".