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Record W2971641483 · doi:10.1140/epja/i2019-12837-8

A novel method for the measurement of half-lives and decay branching ratios of exotic nuclei

2019· article· en· W2971641483 on OpenAlexaff

Bibliographic record

VenueThe European Physical Journal A · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsTRIUMFSaint Mary's University
FundersHelmholtz Graduate School for Hadron and Ion ResearchBundesministerium für Bildung und ForschungJustus Liebig Universität Gießen
KeywordsNuclideBranching fractionExcitationBranching (polymer chemistry)IsotopeDecay productSpectrometer

Abstract

fetched live from OpenAlex

A novel method for simultaneous measurement of masses, Q-values, isomer excitation energies, half-lives and decay branching ratios of exotic nuclei has been demonstrated. The method includes first use of a stopping cell as an ion trap, combining storage of mother and daughter nuclides for variable durations in a cryogenic stopping cell (CSC), and afterwards the identification and counting of them by a multiple-reflection time-of-flight mass spectrometer (MR-TOF-MS). We utilized our method to record the decay and growth of the 216Po and 212Pb isotopes (alpha decay) and of the 119m2Sb isomer ($t_{1/2} = 850\pm 90$ t1/2=850±90 ms) and 119gSb isotope (isomer transition), obtaining half-lives consistent with literature values. The amount of non-nuclear-decay losses in the CSC up to $\sim 10$ ∼10 s is negligible, which exhibits its extraordinary cleanliness. For 119Sb isotopes, we present the first direct measurements of the mass of its ground state, and the excitation energy and decay branching ratios of its second isomeric state (119m2Sb). This resolves discrepancies in previous excitation energy data, and is the first direct evidence that the 119m2Sb isomer decays dominantly via $\gamma$ γ emission. These results pave the way for the measurement of branching ratios of exotic nuclei.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.051
GPT teacher head0.306
Teacher spread0.255 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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