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Record W4408539735 · doi:10.46427/gold2024.23112

Zinc immobilization through sorption to diatomaceous earth

2024· article· en· W4408539735 on OpenAlexaff
Isabelle Hornberger, Janice Kenney

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsMacEwan University
Fundersnot available
KeywordsSorptionZincEarth (classical element)Environmental scienceEnvironmental chemistryChemistryMaterials scienceMetallurgyAdsorptionPhysicsOrganic chemistryAstronomy

Abstract

fetched live from OpenAlex

Zinc contamination can cause severe effects on both terrestrial and aquatic environments, such as a loss of biodiversity in soil or growth inhibition in fish (Singh et al. 2022, Kelly and Tate 1998).This project aims to test the zinc uptake of washed and unwashed diatomaceous earth to better understand what conditions impact it.Zinc concentrations between 0-100 ppm were reacted at a pH range between 3-11 in the presence of diatomaceous earth.The diatomaceous earth was characterized by Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS).SEM-EDS was used to image morphology and determine the elemental composition of the diatomaceous earth and to observe any changes in the system after being exposed to Zn. FTIR spectroscopy was used to probe for surface active functional groups on the diatomaceous earth and determine which functional groups were responsible for binding Zn.Samples were then analyzed by inductively coupled plasma optical emission spectroscopy or ICP-OES to find and quantify metal elements within the solution.These concentrations are then plotted along with negative and positive controls to see the amount of zinc diatomaceous earth sorbed.It was found that as pH increased, the concentration of zinc sorbed increased, and SEM-EDS showed that there was no change in the morphology of the diatomaceous earth after sorption.The speciation of the Zn is pH dependent, being present as a sorbed or dissolved species above pH 7, and this will be important in predicting Zn mobility in freshwater systems.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.895
Threshold uncertainty score0.998

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)0.0010.003

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 head0.025
GPT teacher head0.317
Teacher spread0.292 · 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.

Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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