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Record W2766666115 · doi:10.1093/toxsci/kfx172

Scaling-Up Ionic Liquid-Based Technologies: How Much Do We Care About Their Toxicity? Prima Facie Information on 1-Ethyl-3-Methylimidazolium Acetate

2017· review· en· W2766666115 on OpenAlexafffund
Shaghayegh Ostadjoo, Paula Bertón, Julia L. Shamshina, Robin D. Rogers

Bibliographic record

VenueToxicological Sciences · 2017
Typereview
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsMcGill University
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsPrima facieIonic liquidToxicityScale (ratio)ChemistryBiochemical engineeringComputer scienceBusinessRisk analysis (engineering)Organic chemistryEngineeringPolitical sciencePhysicsLawCatalysis

Abstract

fetched live from OpenAlex

The potential of the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]) to dissolve a variety of biopolymers such as cellulose and chitin, makes it an attractive candidate for scaled-up industrial utilization. In fact, the first steps towards its use at industrial scale have been taken. This increases the urgency to fill the knowledge gaps in its toxicity and environmental impact in order to predict and control its environmental fate. In this mini-review, we discuss the available literature surrounding this key IL. The literature (through the analysis of toxicity of the anion and the cation separately) suggests that [C2mim][OAc] is a relatively safe choice for industrial applications. However, because the IL should be considered as a compound, with unique properties arising from the interactions between the ions, comprehensive toxicity information for this particular IL is still required. To decide, prima facie, if this IL is toxic or not, evaluation of its influence on human health and ecotoxicity is needed prior to its large scale utilization. We chose in this mini-review to focus on toxicity surrounding this IL and evaluate what is known and what is not. Here with all the information in hand, we hope that the urgent need for [C2mim][OAc] toxicological assessment before it can be used in numerous technologies is highlighted. In the near future, we expect that the assessment of toxicity and environmental fate and impact can be integrated directly into any research into the industrial utilization of this IL and any others contemplated for industrial application.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
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 head0.116
GPT teacher head0.348
Teacher spread0.232 · 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 designOther design
Domainnot available
GenreReview

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

Citations62
Published2017
Admission routes2
Has abstractyes

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