Enhanced phytoremediation: A study of mycorrhizoremediation of heavy metal–contaminated soil
Bibliographic record
Abstract
Abstract Arbuscular mycorrhizal fungi (AMF) are microscopic fungi that occur naturally in soil and form a symbiosis with plant roots. By colonizing the roots, the fungus increases plant growth by making soil essential elements like zinc and phosphorus more accessible. AMF can play a role in the phytoremediation of heavy metal–contaminated soil (mycorrhizoremediation). Two research experiments were conducted to evaluate the impact of AMF on the extraction of different heavy metals (arsenic, cadmium, lead, selenium, and zinc) in contaminated soil. A grass mixture composed of Festuca rubra, Festuca eliator, Agropyron repens, and Trifolium repens was used in the experiments, and four different types of AMF were investigated: Glomus intraradices, Glomus mosseae, Glomus etunicatum, and Gigaspora gigantea. The results of the study showed that heavy metal extraction by Glomus intraradices colonized plants was the highest of all four AMF tested and was generally higher than nonmycorrhizal plants, depending on the heavy metal concentration in soil and whether it interacted with other metals in soil. However, metal extraction by AMF colonized grasses reached a plateau after an approximately two‐month period showing no further phytoaccumulation. © 2006 Wiley Periodicals, Inc.
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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 | 0.001 | 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".