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Record W2147107589 · doi:10.1039/b806369a

Removal of metal ions from aqueous solutions using chelating task-specific ionic liquids

2008· article· en· W2147107589 on OpenAlexafffund
Jitendra R. Harjani, Tomislav Friščić, Leonard R. MacGillivray, Robert D. Singer

Bibliographic record

VenueDalton Transactions · 2008
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsSaint Mary's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIonic liquidAlkylAqueous solutionChelationMetalChemistrySolubilityMetal ions in aqueous solutionIonIonic bondingInorganic chemistrySalt (chemistry)Polymer chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

A new class of imidazolium salts with appended aminodiacetic acid moieties as di-tert-butyl esters has been synthesized. An improved synthetic route compared to that previously reported is described. These task specific ionic liquids have been used for the formation of metal chelates with Cu(II), Ni(II) and Co(II) in aqueous solutions. The hydrophobicity and solubility of these metal complexes has been fine-tuned by changing the properties of the imidazolium salts from which they are derived through the introduction of alkyl chains onto the imidazolium core.

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 score0.002

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.045
GPT teacher head0.237
Teacher spread0.192 · 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

Citations75
Published2008
Admission routes2
Has abstractyes

Explore more

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