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Record W7011395096

Mass measurements of neutron-rich nuclides for the astrophysical r process using the Canadian Penning trap mass spectrometer

2022· dissertation· en· W7011395096 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsnot available
Fundersnot available
KeywordsNuclideCaliforniumIsotopePenning trapNeutronr-processNuclear dataMass numberMass spectrometryFission
DOInot available

Abstract

fetched live from OpenAlex

About half of the elements heavier than iron (Z = 26) are believed to be formed via the r process (rapid neutron capture process), of which our understanding is limited. Running theoretical simulations to gain insight into this r process rely on the availability of nuclear data (like nuclear masses, beta decay lifetimes, neutron capture cross sections and others) with reduced uncertainties for nuclides near the expected r-process path. Such data is available in limited capacity due to the challenges in producing those exotic nuclides. The astrophysical conditions required for the r process, and the events that generate them are still open questions. The CAlifornium Rare Isotope Breeder Upgrade (CARIBU) at Argonne National Laboratory (ANL) uses the spontaneous fission from a Californium-252 (252Cf) source and is one the few facilities world-wide to produce beams of such neutron-rich isotopes around the mass numbers A = 105 and A = 140. The extracted ions are subject to multiple stages of cooling and purification, before they are sent to the Canadian Penning trap (CPT) mass spectrometer, where their masses are measured using the Phase-Imaging Ion-Cyclotron- Resonance (PI-ICR) technique. The main focus of this work was to provide data on atomic masses that would allow simulations to replicate the rare-earth peak in the observed r-process abundance pattern. Masses of a total of 34 nuclides are presented in this thesis, of which seven were measured for the first time, including the first-time measurements isotopes of Ce (Z = 58): A = 152−155. The results of these Ce isotopes, with their uncertainties reduced from the extrapolated values of ≥ 200 keV/c2 in the latest Atomic Mass Evaluation (AME2020), to ≤ 6 keV/c2, agree with mass predictions from a reverse engineered Markov Chain Monte Carlo technique for a hot r-process environment, hence validating this “hot” r-process model for this mass region.

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)0.001
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 score0.073
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.275
Teacher spread0.231 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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