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Record W2089838371 · doi:10.1021/jp068542b

Predictions of the Geometries and Fluorescence Emission Energies of Oxyluciferins

2007· article· en· W2089838371 on OpenAlexafffund
Tianxiao Yang, John D. Goddard

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExcited stateSinglet stateEnolComplete active spacePotential energyChemistryAtomic physicsEmission spectrumSpectral lineFluorescenceMolecular physicsPhysicsComputational chemistryBasis setDensity functional theoryQuantum mechanics

Abstract

fetched live from OpenAlex

The complete active space self-consistent field (CASSCF) method and multiconfigurational second-order perturbation theory (CASPT2) have been used to study the structures and spectra of oxyluciferins (OxyLH2). The ground and lowest-lying singlet excited states geometries have been optimized using CASSCF. CASPT2 has been used to predict relaxed emission energies. The focus is on the lowest-lying singlet excited states of the anionic keto and enol forms of OxyLH2(-1) at the optimized excited-state geometries. The planar keto and enol forms of OxyLH2(-1) are minima on both the S0 and the S1 potential energy surfaces. The twisted keto and enol forms of OxyLH2(-1) are transition states on the S0 and S1 potential energy surfaces. The S1 --> S0 fluorescence emission energies are in the range of 54.2-58.4 kcal/mol for the anionic planar keto forms of OxyLH2, and in the range of 55.7-63.2 kcal/mol for the anionic enol forms of OxyLH2. S0 and S1 potential energy surfaces and thus are not implicated in the emission spectra in the gas phase.

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)0.001
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.260
Teacher spread0.253 · 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

Citations38
Published2007
Admission routes2
Has abstractyes

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