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Record W2892272829 · doi:10.1103/physreva.98.052502

Measuring the difference in nuclear charge radius of Xe isotopes by EUV spectroscopy of highly charged Na-like ions

2018· article· en· W2892272829 on OpenAlexafffund
R. Silwal, A. Lapierre, J. D. Gillaspy, Joan Dreiling, S. A. Blundell, Dipti Dipti, A Borovik, G. Gwinner, A. C. C. Villari, Yuri Ralchenko, Endre Takács

Bibliographic record

VenuePhysical review. A/Physical review, A · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute of Standards and TechnologyU.S. Department of CommerceNational Science Foundation
KeywordsAtomic physicsXenonIsotopeCharge radiusIonEffective nuclear chargeSpectroscopyChemistryPhysicsProtonNuclear physics

Abstract

fetched live from OpenAlex

The difference in the mean-square nuclear charge radius of xenon isotopes was measured utilizing a method based on extreme ultraviolet spectroscopy of highly charged Na-like ions. The isotope shift of the Na-like $D1$ ($3s\phantom{\rule{0.16em}{0ex}}^{2}S_{1/2}\ensuremath{-}3p\phantom{\rule{0.16em}{0ex}}^{2}P_{1/2}$) transition between the $^{124}\mathrm{Xe}$ and $^{136}\mathrm{Xe}$ isotopes was experimentally determined using the electron-beam ion-trap facility at the National Institute of Standards and Technology. The mass-shift and the field-shift coefficients were calculated with enhanced precision by the relativistic many-body perturbation theory and multiconfiguration Dirac-Hartree-Fock method. The mean-square nuclear charge radius difference was found to be $\ensuremath{\delta}{\ensuremath{\langle}{r}^{2}\ensuremath{\rangle}}^{136,124}=0.269(42)\phantom{\rule{4pt}{0ex}}{\mathrm{fm}}^{2}$. Our result has smaller uncertainty than previous experimental results and agrees with the literature values.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.015
GPT teacher head0.307
Teacher spread0.292 · 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 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

Citations21
Published2018
Admission routes2
Has abstractyes

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