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Record W3009220195 · doi:10.1002/slct.202000122

Synthesis of New Aza‐ and Thia‐Crown Ether Based Amino Acids

2020· article· en· W3009220195 on OpenAlexaff
Tobias F. Schneider, Nico Brüssow, Alev Yuvanc, Nediljko Budiša

Bibliographic record

VenueChemistrySelect · 2020
Typearticle
Languageen
FieldChemistry
TopicSulfur-Based Synthesis Techniques
Canadian institutionsUniversity of Manitoba
FundersEuropean Commission
KeywordsMoietyCrown etherAmino acidHeteroatomChemistryEtherSulfurOrganic chemistryReagentCombinatorial chemistryIonBiochemistryRing (chemistry)

Abstract

fetched live from OpenAlex

Abstract Crown ethers have been known since the middle of the 20 th century as metal chelating agents with numerous applications. For example, amino acids functionalized with crown ethers have been used to create artificial ion channels. However, only a few of those crown amino acids are known, all of which contain exclusively oxygen as heteroatoms in the crown ether moiety. Alternative structures may be desirable to explore new biological or pharmaceutical applications. Hence, we aim to expand the scope of available crown ether amino acids ‐ in particular those with heteroatoms other than oxygen. Herein we describe the synthesis of three previously unknown amino acids bearing a crown ether moiety. We use two distinct synthetic routes to avoid the use of hazardous reagents. Two of these three amino acids bear sulfur atoms in the crown ether, while the third contains a nitrogen atom.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0010.001

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 head0.021
GPT teacher head0.240
Teacher spread0.218 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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