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Record W2038539309 · doi:10.1002/qua.20051

Strutinsky's shell‐correction method in the extended Kohn–Sham scheme for the investigation of binding energies of atoms and cations in the ground state

2004· article· en· W2038539309 on OpenAlexaff
Ya. I. Delchev, Alexander I. Kuleff, Tzonka Mineva, Federico Zahariev, J. Maruani

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of British Columbia
FundersCentre National de la Recherche Scientifique
KeywordsGround stateChemistrySeries (stratigraphy)Shell (structure)Binding energyAtomic physicsKohn–Sham equationsState (computer science)QuantumOrder (exchange)Energy (signal processing)Scheme (mathematics)PhysicsComputational chemistryQuantum mechanicsDensity functional theoryMaterials scienceMathematicsMathematical analysisAlgorithm

Abstract

fetched live from OpenAlex

Abstract We performed self‐consistent calculations of the oscillating part of the ground‐state energy of atoms and cations from Be through Ca, using Strutinsky's shell‐correction method in the framework of the extended Kohn–Sham scheme. New “transition state” numbers in the Taylor series expansion of the ground‐state energy are introduced, allowing the elimination of the second‐order shell‐correction term. We show that the application of this procedure yields practically identical results whether it is performed self‐consistently or not, and even the first‐order term of the shell‐correction series gives a good approximation. Oscillations in the shell‐correction energy of cations appear amplified with respect to those of the corresponding isoelectronic neutral atoms. © 2004 Wiley Periodicals, Inc. Int J Quantum Chem, 2004

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)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.316
Teacher spread0.297 · 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

Citations3
Published2004
Admission routes1
Has abstractyes

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