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Record W2461803336 · doi:10.2166/wqrj.2007.015

Sorption of Heavy Metals with Sol-Gel Particles Containing Crude Metallothionein Extracts from Scchizosaccharomyces pombe

2007· article· en· W2461803336 on OpenAlexaff
Shirin Bahrami, Amarjeet Bassi, Ernest K. Yanful

Bibliographic record

VenueWater Quality Research Journal · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsWestern University
Fundersnot available
KeywordsCadmiumChemistryZincAdsorptionDesorptionMetallothioneinSorptionLangmuir adsorption modelNuclear chemistryChromatographyLangmuirOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Crude metallothionein (MT) extracts from Scchizosaccharomyces pombe entrapped in sol-gels were investigated for the removal of heavy metals such as cadmium and zinc. The sol-gel provided a robust immobilization matrix for the protein extract. Adsorption and desorption isotherms were developed for both cadmium and zinc. Both metals were recovered from the sol-gel by desorption using a 1 M NaCl solution. The adsorption kinetic studies showed that cadmium and zinc adsorption followed the Langmuir isotherm. The distribution factors for cadmium and zinc were found to be 5.43 L/mg and 2.88 L/mg, respectively. Greater than 60% of Zn2+ was also removed using MT sol-gels. The experiments demonstrated that MT has a greater capacity for Cd than polyethyleneimine immobilized in the sol-gels. The adsorption capacity of MT was found to be 588.2 mg of cadmium and 434.8 mg of zinc per gram of immobilized MT, which is significantly higher than with nonbiological chelators such as polyethyleneimine or EDTA.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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 head0.112
GPT teacher head0.377
Teacher spread0.265 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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