Phytoremediation - A sustainable approach for contaminant remediation in arid and semi-arid regions ? a review
Bibliographic record
Abstract
Existing information relating to the application of phytoremediation in arid regions, for mitigating the toxicity of organic and inorganic contaminants is summarized, emphasizing the comparative merits of different phytostrategies. Adverse climatic conditions in arid and semi-arid environments along with the intrinsic abiotic stresses need specific considerations, which are discussed here. The current "state of art" for petrochemical and metal phytoremediation, as well as phytodesalination is presented, making it possible to choose the very best decision, when the technology is applied for various contaminant scenarios. Information is also provided on contaminants in arid regions, remediation approaches and different phytoremediation strategies to be adopted, depending on the nature of contaminants and the site situations. Furthermore, phytodesalination may well occur in parallel with phytoremediation of heavy metal polluted soils in arid regions, enhancing the potential of this process. This has drawn a great deal of interest during recent years and is reviewed here. Finally, the lacunae in the current knowledge are identified, which has to be addressed to improve the effectiveness of phytoremediation under arid conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".