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First Use of High Charge States for Mass Measurements of Short-Lived Nuclides in a Penning Trap

2011· article· en· W1986610776 on OpenAlexaff
S. Ettenauer, M. C. Simon, A. T. Gallant, T. Brunner, U. Chowdhury, V. V. Simon, M. Brodeur, A. Chaudhuri, E. Mané, C. Andreoiu, G. Audi, J. R. Crespo López-Urrutia, P. P. J. Delheij, G. Gwinner, A. Lapierre, D. Lunney, M. R. Pearson, R. Ringle, J. Ullrich, J. Dilling

Bibliographic record

VenuePhysical Review Letters · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomical and nuclear sciences
Canadian institutionsSimon Fraser UniversityUniversity of ManitobaUniversity of British ColumbiaTRIUMF
Fundersnot available
KeywordsPenning trapNuclideAtomic physicsPhysicsIon trapIonNuclear physicsElectron beam ion trapElectronIsotopeAtomic massElectron captureExcitationCathode ray

Abstract

fetched live from OpenAlex

Penning trap mass measurements of short-lived nuclides have been performed for the first time with highly charged ions, using the TITAN facility at TRIUMF. Compared to singly charged ions, this provides an improvement in experimental precision that scales with the charge state q. Neutron-deficient Rb isotopes have been charge bred in an electron beam ion trap to q=8-12+ prior to injection into the Penning trap. In combination with the Ramsey excitation scheme, this unique setup creating low energy, highly charged ions at a radioactive beam facility opens the door to unrivaled precision with gains of 1-2 orders of magnitude. The method is particularly suited for short-lived nuclides such as the superallowed β emitter 74Rb (T(1/2)=65 ms). The determination of its atomic mass and an improved Q(EC) value are presented.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.110
GPT teacher head0.289
Teacher spread0.179 · 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

Citations69
Published2011
Admission routes1
Has abstractyes

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