Phytoremediation of contaminated soils using ornamental plants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Phytoremediation has attracted increasing attention and is a promising technology for addressing soil contamination problems. Unlike other kinds of remediation plants, ornamental plants grown for decorative purposes in gardens and landscape design projects have been an important source of remediation plants in recent years. In addition to beautifying the environment, some ornamental plants can not only grow well but also accumulate or degrade contaminants when growing in soil contaminated with heavy metals or organic pollutants. Especially in contaminated urban areas, it is comparatively rare and commendable when remediation plants with ornamental value are applied. In this review, we summarized the current research on the phytoremediation of contaminated soils using ornamental plants, evaluated the phytoremediation capacity of ornamental plants in heavy-metal and organic pollutant-contaminated soils, and highlighted specific ornamental plants with a strong accumulation ability and tolerance to pollutants. The findings related to the main mechanisms of the phytoremediation of contaminated soils were explained. Enhancement measures aimed at promoting the bioavailability of contaminants and the tolerance of ornamental plants were also reviewed in this article. It is hoped that this study will draw attention to a new path for phytoremediation technology.
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.
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 it