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Record W7039765975

Nuclear moments of the radioactive isotope 131La determined by collinear fast-beam laser spectroscopy

2006· article· en· W7039765975 on OpenAlexaboutno aff

Bibliographic record

VenueLirias (KU Leuven) · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsnot available
Fundersnot available
KeywordsIsotopeNeutronRadionuclideNuclear structureProtonSpectroscopyNuclear reactionRadioactive decay
DOInot available

Abstract

fetched live from OpenAlex

We report on our first measurements with collinear fast-beam spectroscopy at the ISAC facility at TRIUMF (Canada). This nuclear facility is able to produce intense beams of radioactive isotopes of the rare earth elements with unprecedented intensities. In particular the neutron deficient region below the N=82 shell closure is of interest and contains around N=74 an unexplored region of nuclear deformation predicted both by the Finite-Range Droplet Model (FRDM) and the Hartree-Fock-BCS method. These calculations do not include the triaxial degree of freedom. However, also triaxiality or γ-softness is predicted theoretically to play an important role in the nuclei of the low Z elements in the rare earth region N=74. The nuclear moments and changes in nuclear charge radii provide sensitive information on nuclear deformation. So far only a few rare earth isotopes below shell closure could be investigated with laser spectroscopy. This is due to the low production yields, which require large proton beam currents for the sufficient production of radioactive isotopes in this region. In this paper, we report preliminary measurements of the HFS constants of 131La (N=74) as an initial step to further exploring this region. The nuclear moments are extracted from the data and compared with predictions from the above listed theoretical models. our work is an extension of our earlier off-line experiments on 135,137-139La at JAEA (Japan) to on-line laser spectroscopy.

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: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.767

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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