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Record W4385271830 · doi:10.1080/00268976.2023.2232051

Calculation of the local environment of a barium monofluoride molecule in a neon matrix

2023· article· en· W4385271830 on OpenAlexafffund
R. Lambo, G. K. Koyanagi, M. Horbatsch, R. Fournier, E. A. Hessels

Bibliographic record

VenueMolecular Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaJohn Templeton FoundationGordon and Betty Moore FoundationAlfred P. Sloan Foundation
KeywordsNeonAtomic physicsChemistryMoleculeTriatomic moleculeDipoleCoupled clusterNoble gasBasis setAtom (system on chip)PhysicsArgon

Abstract

fetched live from OpenAlex

The local environment of a barium monofluoride (BaF) molecule embedded in a neon matrix is studied theoretically. The energy of the BaF-Ne triatomic system is calculated with a scalar relativistic Hamiltonian, using coupled-cluster theory at the CCSD(T) level for 1625 positions of the Ne atom relative to the BaF molecule. The calculations are repeated with increasing basis sets (from double to quintuple zeta), and are extrapolated to estimate the complete-basis-set limit. Using the potential obtained from these calculations, it is determined that substituting a BaF molecule for ten Ne atoms is favoured compared to substitutions for other numbers of Ne atoms. The equilibrium position and orientation of the BaF molecule and the displacement of its nearby Ne neighbours are determined. The potential barriers that prevent the BaF molecule from migrating and rotating are calculated. These barriers are essential for the EDM3 collaboration, which is using BaF molecules embedded in a noble-gas solid to perform a precision measurement of the electron electric dipole moment.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.005
GPT teacher head0.230
Teacher spread0.225 · 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 designTheoretical or conceptual
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

Citations8
Published2023
Admission routes2
Has abstractyes

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