Willow vegetation filters for wastewater treatment and soil remediation combined with biomass production
Bibliographic record
Abstract
Vegetation filters of fast-growing trees such as willows and poplars are becoming important as an alternative to conventional treatment of wastewater and landfill leachate. Short-rotation willow coppice is a non-edible crop and has many of the requirements for a suitable vegetation filter. The filtering capacity (e.g., of nitrogen) is very high, and the crop promotes denitrification in the root zone. It has a highly selective uptake of heavy metals, especially cadmium, which enables remediation of contaminated soils. In addition, willows have a high evapotranspiration rate facilitating high loads, e.g., of polluted landfill leachate. Because of the pathogens present in municipal wastewater and sludge, special attention must be paid to storage and distribution of wastewater. In many cases vegetation filters are more cost-effective than conventional treatment methods and also facilitate recycling of valuable resources in society. Key words: bioenergy, economics, heavy metals, landfill leachates, municipal wastewater, pathogens, Salix spp., sewage sludge, wood ash
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 0.001 |
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".