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Record W2003683774 · doi:10.1002/jcc.20699

Vertical excitation energies for ribose and deoxyribose nucleosides

2007· article· en· W2003683774 on OpenAlexaff
Remmick So, Saman Alavi

Bibliographic record

VenueJournal of Computational Chemistry · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsSteacie Institute for Molecular SciencesCarleton University
Fundersnot available
KeywordsDeoxyriboseChemistryExcited stateRiboseTime-dependent density functional theoryNucleosideDensity functional theoryExcitationMoietyNucleobaseNucleic acidUracilComputational chemistryMoleculeStereochemistryDNAAtomic physicsOrganic chemistryPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Vertical excitation energies for DNA and RNA nucleosides are determined with electron structure calculations using the time-dependent density functional theory (TDDFT) method at the B3LYP/6-311++G(d,p) level for nucleoside structures optimized at the same level of theory. The excitation energies and state assignments are verified using B3LYP/aug-cc-pVDZ level calculations. The nature of the first four excited states of the nucleosides are studied and compared with those of isolated bases. The lowest npi* and pipi* transitions in the nucleoside remain localized on the aromatic rings of the base moiety. New low-energy npi* and pisigma* transitions are introduced in the nucleosides as a result of bonding to the ribose and deoxyribose molecules. The effect on the low-lying excited state transitions of the binding to phosphate groups at the 5'- and 3',5'-hydroxyl sites of the uracil ribose nucleoside are also studied. Some implications of these calculations on the de-excitation dynamics of nucleic acids are discussed.

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 score0.012
Threshold uncertainty score0.413

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 head0.258
Teacher spread0.251 · 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

Citations26
Published2007
Admission routes1
Has abstractyes

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