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Record W2169941438 · doi:10.1139/b01-012

Copper uptake in <i>Typha latifolia</i> as affected by iron and manganese plaque on the root surface

2001· article· en· W2169941438 on OpenAlexvenueno aff
Z.H. Ye, K. Cheung, Ming Hung Wong

Bibliographic record

VenueCanadian Journal of Botany · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsnot available
FundersResearch Grants Council, University Grants CommitteeUniversity Grants CommitteeUniversity of Hong KongHong Kong Baptist University
KeywordsManganeseTyphaCopperChemistryMetalAdsorptionNuclear chemistryEnvironmental chemistryBotanyWetlandBiology

Abstract

fetched live from OpenAlex

The effects of iron (Fe) and manganese (Mn) plaque on the accumulation of copper (Cu) in Typha latifolia L. were investigated under laboratory conditions in nutrient solution cultures. Seedlings with and without Fe plaque on their roots, induced with 15 or 60 µg·mL –1 Fe, were exposed to 0.04, 0.12, or 0.36 µg·mL –1 Cu solutions, and seedlings with and without Mn plaque, induced with 15 or 60 µg·mL –1 Mn, were exposed to 0.12 or 0.36 µg·mL –1 Cu solutions for 24 days, respectively. In all cases, the amount and proportion of Cu adsorbed on the root surface increased with a higher concentration of Cu in the solutions. In the presence of Fe or Mn, T. latifolia adsorbed more Cu and had a higher proportion of Cu on its roots, especially the roots with heavy Mn or Fe plaque. Although more Fe than Mn accumulated on the roots in the form of plaque, the Mn plaque adsorbed more Cu. The data suggest that root plaque can act as a Cu reservoir, depending on the amount of Fe or Mn on the roots and the amount of Cu in the environment.Key words: wetland plant, heavy metal uptake, cattail, iron plaque, manganese plaque.

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)0.000
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 score0.610
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.186
Teacher spread0.176 · 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

Citations65
Published2001
Admission routes1
Has abstractyes

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