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Record W2553449019 · doi:10.1063/1.4967813

Vertical excitation energies from the adiabatic connection

2016· article· en· W2553449019 on OpenAlexafffund
Axel D. Becke

Bibliographic record

VenueThe Journal of Chemical Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaKillam TrustsDalhousie UniversityMcMaster University
KeywordsAdiabatic processExcitationExcited stateConnection (principal bundle)Open shellAdiabatic theoremPhysicsDensity functional theoryPerturbation theory (quantum mechanics)Singlet stateElectronSimple (philosophy)Quantum mechanicsWork (physics)Statistical physicsAtomic physicsMathematicsGeometry

Abstract

fetched live from OpenAlex

Vertical single-particle excitations from closed-shell ground states are complicated by the fact that the singlet open-shell states are, even in the first approximation, two-determinantal. Thus two-electron integrals come into play and standard time-independent DFT (density-functional theory) does not apply. In this work, we use the "adiabatic connection" to analyse the role of the two-electron integrals, obtaining a time-independent DFT approach to excitation-energy calculations that is new and simple. A non-empirical modeling of the method works as well as the popular TD-B3LYP time-dependent approach to excited states, and can be made even simpler by introducing one reasonable semi-empirical parameter.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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

Citations30
Published2016
Admission routes2
Has abstractyes

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