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Record W2006038145 · doi:10.1080/15226510903353179

Effect of Amendments on Phytoavailability and Fractionation of Copper and Zinc in a Contaminated Soil

2010· article· en· W2006038145 on OpenAlexafffund
Prabha K. Padmavathiamma, Loretta Y. Li

Bibliographic record

VenueInternational Journal of Phytoremediation · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Environment
KeywordsLolium perenneFestuca rubraPoa pratensisLimeAgronomySoil waterChemistrySoil conditionerAmendmentFestuca arundinaceaPerennial plantSoil pHZincEnvironmental chemistryEnvironmental sciencePoaceaeBiologySoil science

Abstract

fetched live from OpenAlex

The ability of amendments to modify the soil properties and influence plants to immobilise Cu and Zn was studied in a naturally contaminated, additionally spiked podzolic soil. Lolium perenne L (perennial rye grass), Festuca rubra L (creeping red fescue) and Poa pratensis L (Kentucky blue grass) were tested in a pot study in the presence of soil amendments (lime, phosphate, and compost, individually and in combination) to assess the effect of soil-plant-amendment interaction on phytostabilisation. The ability of treatments to stabilize metals was assessed on the basis of metal fractionation in soil, partitioning of metals in plants, and metal uptake by the plants. Significant partitioning of Cu into immobile forms occurred as a result of the growth of Festuca rubra, and of Zn by the growth of Poa pratensis. Application of lime significantly reduced the exchangeable fraction of Zn, whereas phosphate application had an accelerating effect on exchangeable Cu. With combined application of amendments, the plant metal concentration decreased by more than 40% for Cu and 70% for Zn, compared to soils receiving no amendments. Combined application of amendments, in conjunction with growth of Festuca and Poa, can be recommended for phytostabilising of Cu and Zn in moderately contaminated acid soils of southwest British Columbia.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.258
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2010
Admission routes2
Has abstractyes

Explore more

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