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Record W2257364489 · doi:10.5539/ijc.v8n1p102

Structural Modeling of Glutathiones Containing Selenium and Tellurium

2016· article· en· W2257364489 on OpenAlexvenueno aff
Valter Aragão do Nascimento, Petr Melnikov, Andre Vidal Dabela Lanoa, Anderson F. Silva, Lourdes Z. Z. Consolo

Bibliographic record

VenueInternational Journal of Chemistry · 2016
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicOrganoselenium and organotellurium chemistry
Canadian institutionsnot available
FundersFundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do SulConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsChalcogenChemistryTelluriumBond lengthSeleniumCrystallographyMolecular geometryIonic bondingMoleculeCrystal structureOrganic chemistryIon

Abstract

fetched live from OpenAlex

The comparative structural modeling of reduced and oxidized glutathiones, as well as their derivatives containing selenium and tellurium in chalcogen sites (Ch = Se, Te) has provided detailed information about the bond lengths and bond angles, filling the gap in the structural characteristics of these tri-peptides. The investigation using the molecular mechanics technique with good approximation confirmed the available information on X-ray refinements for the related compounds. It was shown that Ch-H and Ch-C bond lengths grow in parallel with the increasing chalcogen ionic radii. Although the distances C-C, C-O, and C-N are very similar, the geometry of GChChG glutathiones is rich in conformers owing to the possibility of rotation about the bridge Ch-Ch. It is confirmed that the distances Ch-Ch are essentially independent of substituents in most of chalcogen compounds from elemental chalcogens to oxydized glutathiones. The standard program Hyperchem 7.5 has proved to be an appropriate tool for the structural description of less-common bioactive compositions when direct X-ray data are missing.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.049
GPT teacher head0.373
Teacher spread0.323 · 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 designSimulation or modeling
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

Citations0
Published2016
Admission routes1
Has abstractyes

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