A novel vegetated three-layer landfill cover system using recycled construction wastes without geomembrane
Bibliographic record
Abstract
To promote environmental protection and sustainability, the use of plants and recycled wastes in geotechnical construction such as landfill covers is recommended. A landfill cover field test was conducted at the Shenzhen Xiaping landfill site, located in a humid climatic region of China. The main objective was to validate the field performance of a novel vegetated three-layer landfill cover system using recycled construction waste without the need of geomembrane. Unsieved completely decomposed granite and coarsely crushed concrete was used for the top and intermediate layers while sieved completely decomposed granite was used as the lowest layer. One section was transplanted with Bermuda grass while the other section was left bare. To assess the landfill cover performance, pore-water pressure, volumetric water content, percolation, and atmospheric parameters were measured for a period of 13 months under natural climatic conditions. The cumulative rainfall depth was about 2950 mm over the entire monitoring period. During rainfall, the presence of grass led to lower pore-water pressure (or higher suction) and volumetric water content in the three-layer landfill cover system. At the end of monitoring, the cumulative percolation was about 27 and 20 mm for the bare and grass-covered landfill covers, respectively. It is evident that the vegetated three-layer landfill cover system using recycled concrete without geomembrane can be effective in minimizing percolation in humid climates.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".