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Record W3190478050 · doi:10.3390/molecules26164791

Applications of Ionic Liquids in Whole-Cell and Isolated Enzyme Biocatalysis

2021· review· en· W3190478050 on OpenAlex
Hasan T. Imam, Vladimír Krasňan, Martin Rebroš, Andrew C. Marr

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMolecules · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsnot available
FundersEuropean Regional Development FundEngineering and Physical Sciences Research CouncilQueen's UniversityQueen's University Belfast
KeywordsIonic liquidBiocatalysisIonic bondingChemistryBiochemical engineeringNanotechnologyMaterials scienceOrganic chemistryCatalysisEngineeringIon

Abstract

fetched live from OpenAlex

Ionic liquids have unique chemical properties that have fascinated scientists in many fields. The effects of adding ionic liquids to biocatalysts are many and varied. The uses of ionic liquids in biocatalysis include improved separations and phase behaviour, reduction in toxicity, and stabilization of protein structures. As the ionic liquid state of the art has progressed, concepts of what can be achieved in biocatalysis using ionic liquids have evolved and more beneficial effects have been discovered. In this review ionic liquids for whole-cell and isolated enzyme biocatalysis will be discussed with an emphasis on the latest developments, and a look to the future.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.274
Teacher spread0.263 · 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