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Record W4232811896 · doi:10.1002/qua.22007

On variational estimates for exchange‐correlation interaction obtained within super‐CI approach to MCSCF approximation

2009· article· en· W4232811896 on OpenAlexaff
Sergey Gusarov, Tatiana Fedorova, Yuri Yu. Dmitriev, Andriy Kovalenko

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of AlbertaNational Institute for Nanotechnology
Fundersnot available
KeywordsHermitian matrixBrillouin zoneFormalism (music)Hartree–Fock methodQuantum mechanicsAtomic orbitalConfiguration interactionDensity matrixSingular value decompositionMatrix (chemical analysis)Full configuration interactionMathematical physicsComputational chemistryMathematicsPhysicsChemistryQuantumMolecule

Abstract

fetched live from OpenAlex

Abstract Variation approximations for the exchange‐correlation interaction are considered which can be obtained when necessary conditions of the generalized Brillouin's theorem are fulfilled. It is done in the post‐Hartree–Fock approach to the electronic structure theories. The corresponding approximations appear within the two‐step Super‐CI self‐consistent procedure of the MCSCF one‐particle optimization. The basic formalism used is in close connection with the formalism of the extended Koopmans' theorem but here the extended Koopmans' matrix itself is calculated in a self‐consistent way. It is based on the singular value decomposition of the Koopmans' matrix. The final hermitian Koopmans' matrix satisfies the conditions of the generalized Brillouin's theorem. It commutes with the density matrix and equations for self‐consistent orbitals are transformed to the generalized Hartree–Fock equations with additional hermitian exchange correlation matrix. This matrix is interpreted as a matrix of the exchange‐correlation interaction. © 2009 Wiley Periodicals, Inc. Int J Quantum Chem, 2009

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: none
Teacher disagreement score0.608
Threshold uncertainty score0.659

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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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