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Record W2898616983 · doi:10.3390/molecules23112859

Amide Activation in Ground and Excited States

2018· article· en· W2898616983 on OpenAlexaff
Ervin Kovács, Balázs Rózsa, Attila Csomos, Imre G. Csizmadia, Zoltán Mucsi

Bibliographic record

VenueMolecules · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversity of Toronto
FundersNemzeti Kutatási, Fejlesztési és Innovaciós AlapHungarian Scientific Research Fund
KeywordsAmideSimplicityChemistryComputer scienceExcited stateSimple (philosophy)Interpretation (philosophy)Combinatorial chemistryBiochemical engineeringComputational chemistryQuantum chemicalPeptide bondMoleculeOrganic chemistryEpistemologyPhysicsEngineeringPhilosophy

Abstract

fetched live from OpenAlex

Not all amide bonds are created equally. The purpose of the present paper is the reinterpretation of the amide group by means of two concepts: amidicity and carbonylicity. These concepts are meant to provide a new viewpoint in defining the stability and reactivity of amides. With the help of simple quantum-chemical calculations, practicing chemists can easily predict the outcome of a desired process. The main benefit of the concepts is their simplicity. They provide intuitive, but quasi-thermodynamic data, making them a practical rule of thumb for routine use. In the current paper we demonstrate the performance of our methods to describe the chemical character of an amide bond strength and the way of its activation methods. Examples include transamidation, acyl transfer and amide reductions. Also, the method is highly capable for simple interpretation of mechanisms for biological processes, such as protein splicing and drug mechanisms. Finally, we demonstrate how these methods can provide information about photo-activation of amides, through the examples of two caged neurotransmitter derivatives.

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 score0.016
Threshold uncertainty score0.219

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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

Citations44
Published2018
Admission routes1
Has abstractyes

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