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Record W1967395235 · doi:10.1504/ijewm.2013.050517

Influence of phosphate and citric acid on the phytoextraction of As from contaminated soils

2012· article· en· W1967395235 on OpenAlexaff
Ji hyun Kwak, Kihong Park, Pei chun Chang, Wenju Liu, Ju-Yong Kim, Kyoung‐Woong Kim

Bibliographic record

VenueInternational Journal of Environment and Waste Management · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsUniversity of Waterloo
FundersGwangju Institute of Science and Technology
KeywordsPteris vittataCitric acidPhosphateFernArsenicChemistryFrondEnvironmental chemistrySoil waterPhytoremediationSoil contaminationPhosphoriteBotanyHyperaccumulatorFood scienceEnvironmental scienceBiologyBiochemistryHeavy metalsOrganic chemistry

Abstract

fetched live from OpenAlex

The influence of phytoextraction in arsenic (As) contaminated soil on the phosphate and citric acid addition were investigated using Pteris vittata L. (Chinese brake fern). The As uptake in the fronds increased 85% in As-spiked soil when phosphate was added. The addition of citric acid for 2 weeks to the phosphate added soils resulted in the highest As uptake by 75% compared to only phosphate treatment. The Zn concentrations in fronds also increased 31-fold in phosphate added soils and 60-fold in 2-week citric acid added soils without phosphate treatment. The extractable arsenic species in the fern fronds are 71% of As (III) and 29% of As (V), respectively.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2012
Admission routes1
Has abstractyes

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