Treatment of Salted Road Runoffs Using <i>Typha latifolia, Spergularia canadensis</i>, and <i>Atriplex patula</i>: A Comparison of Their Salt Removal Potential
Bibliographic record
Abstract
Abstract De-icing salts are used all around the world to improve driving security. Their impacts on the environment are a major concern, especially due to the production of salted road runoffs that induce rising of salinity of freshwater ecosystems. Some plants tolerate high salt concentrations and are able to accumulate large amounts of salt in their tissues. To protect freshwater ecosystems, constructed wetland incorporating this kind of plant could be used to treat salted road runoffs before they reached natural ecosystems. Lake Saint-Augustin, located near Quebec City (Quebec, Canada) is used as an experimental watershed area. Typha latifolia, Atriplex patula, and Spergularia canadensis have been selected and assessed for their ability to survive and grow in salted waters by accumulating salt in their tissues. Germination (20 days) experiments, recovery experiments (20 days), and chloride accumulation experiments (2 months) have been performed in a controlled environment. The three species showed no germination inhibition for salt concentrations found in the field (0, 150, 1500 mg NaCl/L). Accumulation of chloride has been found significant for all species. Typha latifolia showed the best accumulation of chloride (63 mgCl−/g of dry mass) which corresponds to a standing stock up to 230,000 mgCl⋅m2. This result is promising and supports the decision for upgrading the process to a constructed wetland.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".