High Carbon Wood Ash Impact on Grass Uptake of Per- and Polyfluoroalkyl Substances from Contaminated Agricultural Soils
Bibliographic record
Abstract
In a one-year greenhouse study, a low-cost high-carbon wood ash was mixed at 1.5, 3.0, and 6.0 wt % into a per- and polyfluoroalkyl substance (PFAS)-contaminated farm soil to evaluate PFAS uptake into perennial forage grasses across five harvest cycle. Wood ash significantly reduced ( p <0.05) grass uptake of several short- and long-chain PFASs. For the highly bioaccumulating perfluorooctanesulfonate, grass leaves from the 6 wt % wood ash treatment exhibited markedly lower translocation factors than those from the no-ash control ( p <0.001), e.g., >71% reduction through all harvests. Moreover, the 6 wt % treatment produced taller grass leaves and higher biomass yields ( p <0.05) relative to other treatments and the control. This potted plant study demonstrated the potential for high-carbon wood ash to reduce PFAS availability to plants while also enhancing plant growth; however, field-based studies are needed to determine if these benefits are sustained under field conditions.
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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".