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Record W2982105445 · doi:10.1002/cbic.201900567

Mechanoenzymatic Transformations in the Absence of Bulk Water: A More Natural Way of Using Enzymes

2019· review· en· W2982105445 on OpenAlex
Sandra Kaabel, Tomislav Friščić, Karine Auclair

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemBioChem · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsMcGill University
Fundersnot available
KeywordsAqueous solutionChemistryStereospecificityStereoselectivityEnzymeSolventOrganic chemistryEnzyme catalysisOrganic solventBiocatalysisChemical engineeringCombinatorial chemistryBiochemical engineeringCatalysisReaction mechanism

Abstract

fetched live from OpenAlex

Mechanochemical enzymatic reactions without bulk water have emerged as a low-waste and efficient method to access useful chemicals and to depolymerize biomass components in a single step. This emergent mechanoenzymatic reaction strategy is able to take advantage of the stereospecificity, regio- and stereoselectivity, as well as renewability of enzymes, while avoiding bulk solvents, offering the opportunity to control the direction of the reaction, bypassing reactant solubility issues, and enabling reactions with water-sensitive substrates or products. Enzymes are traditionally used in dilute aqueous solution, which is quite different from their crowded, water-depleted natural environment. This review outlines recent work which demonstrates that enzymes can be equally or even more efficient under mechanochemical conditions, without bulk aqueous or organic solvent.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.197
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.291
Teacher spread0.258 · 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