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Record W2081075534 · doi:10.3390/molecules181214739

Examination of the Potential for Adaptive Chirality of the Nitrogen Chiral Center in Aza-Aspartame

2013· article· en· W2081075534 on OpenAlexafffund
Samir Bouayad‐Gervais, William D. Lubell

Bibliographic record

VenueMolecules · 2013
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaUniversité de Montréal
KeywordsAspartameChemistryRacemizationChirality (physics)Residue (chemistry)ThaumatinAsparagineNitrogenStereochemistryOrganic chemistryFood scienceBiochemistryEnzyme

Abstract

fetched live from OpenAlex

The potential for dynamic chirality of an azapeptide nitrogen was examined by substitution of nitrogen for the α-carbon of the aspartate residue in the sweetener S,S-aspartame. Considering that S,S- and R,S-aspartame possess sweet and bitter tastes, respectively, a bitter-sweet taste of aza-aspartame 9 could be indicative of a low isomerization barrier for nitrogen chirality inter-conversion. Aza-aspartame 9 was synthesized by a combination of hydrazine and peptide chemistry. Crystallization of 9 indicated a R,S-configuration in the solid state; however, the aza-residue chiral center was considerably flattened relative to its natural amino acid counterpart. On tasting, the authors considered aza-aspartame 9 to be slightly bitter or tasteless. The lack of bitter sweet taste of aza-aspartame 9 may be due to flattening from sp2 hybridization in the urea as well as a high barrier for sp3 nitrogen inter-conversion, both of which may interfere with recognition by taste receptors.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.151

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.227
Teacher spread0.216 · 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.

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

Citations17
Published2013
Admission routes2
Has abstractyes

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