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Record W2328933905 · doi:10.1021/jp503099m

Simulation of the Resonance Raman Spectrum for Uracil

2014· article· en· W2328933905 on OpenAlexaff
Shuai Sun, Alex Brown

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2014
Typearticle
Languageen
FieldChemistry
TopicMolecular Spectroscopy and Structure
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUracilRaman spectroscopyResonance (particle physics)Spectrum (functional analysis)Nuclear magnetic resonancePhysicsMolecular physicsAtomic physicsChemistryOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

The resonance Raman spectrum of uracil is simulated using the Herzberg-Teller short-time dynamics formalism. The ground-state geometry is optimized at the levels of PBE0/aug-cc-pVTZ and B3LYP/aug-cc-pVTZ, respectively. The gradient of the bright excited state is computed using time-dependent density functional theory and spin-flip time-dependent density functional theory. The excited-state calculations are carried out in both the gas phase and implicit water using the conductor-like polarizable continuum model. The ground-state equilibrium structure is found to impact the resulting resonance Raman spectrum significantly. The simulated resonance Raman spectrum using the long-range corrected functionals, that is, CAMB3LYP and LC-BLYP, and based on the PBE0/aug-cc-pVTZ optimized ground-state structure shows better agreement with the experimental spectrum than using standard hybrid functionals, that is, PBE0 and B3LYP. The solvation effect leads to a change in the energetic order of the n → π* and π → π* excited states, and it improves the agreement with the experimental spectrum, especially with regard to the relative intensities of the peaks with frequencies greater than 1600 cm(-1).

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 score0.024
Threshold uncertainty score0.222

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 head0.248
Teacher spread0.243 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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