Retention of Three Heavy Metals (Zn, Pb, and Cd) in a Calcareous Soil Controlled by the Modification of Flow with Geotextiles
Bibliographic record
Abstract
Although geotextiles are increasingly employed in stormwater infiltration basins, their influence on the flow and transfer of contaminants, such as heavy metals, has not been fully investigated. Leaching column experiments were conducted to characterize the flow and transfer of three heavy metals (zinc, lead, and cadmium) in a calcareous soil with and without geotextiles under steady-state flow and close to saturation forthe soil. The influence of geotextiles was characterized for two types of geotextiles (needlepunched and thermosealed) and for two different initial saturation degrees for the needlepunched geotextile. The main results showed that, when placed wet, the needlepunched geotextile had no influence. When placed dry, it homogenized the flow in its surroundings and thus allowed better contact between heavy metals and the reactive soil, resulting in an increase of their retention. The thermosealed geotextile, placed dry, homogenized the flow and increased retention over a larger area, resulting in optimal global retention. In conclusion, geotextiles could be used in infiltration basins, provided that their effect on both flow and heavy metal retention is optimized by appropriate design--choice of geotextiles--and appropriate monitoring--control of hydric conditions.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".