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Precision Mass Measurements of Neutron-Rich Neodymium and Samarium Isotopes and Their Role in Understanding Rare-Earth Peak Formation

2018· article· en· W2811271699 on OpenAlexafffundabout
R. Orford, Nicole Vassh, J. A. Clark, G. C. McLaughlin, Matthew R. Mumpower, G. Savard, Rebecca Surman, A. Aprahamian, F. Buchinger, M. T. Burkey, D. Gorelov, T. Hirsh, J. Klimeš, G. Morgan, A. Nystrom, K. S. Sharma

Bibliographic record

VenuePhysical Review Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsUniversity of ManitobaMcGill University
FundersArgonne National LaboratoryNuclear PhysicsUniversity of Notre DameU.S. Department of EnergyLos Alamos National LaboratoryNatural Sciences and Engineering Research Council of CanadaNational Nuclear Security AdministrationOffice of ScienceNational Science Foundation
KeywordsSamariumr-processPhysicsIsotopeCaliforniumNuclear physicsNeutronAtomic physicsNucleosynthesisNuclear reaction

Abstract

fetched live from OpenAlex

The Canadian Penning Trap mass spectrometer at the Californium Rare Isotope Breeder Upgrade (CARIBU) facility was used to measure the masses of eight neutron-rich isotopes of Nd and Sm. These measurements are the first to push into the region of nuclear masses relevant to the formation of the rare-earth abundance peak at A∼165 by the rapid neutron-capture process. We compare our results with theoretical predictions obtained from "reverse engineering" the mass surface that best reproduces the observed solar abundances in this region through a Markov chain Monte Carlo technique. Our measured masses are consistent with the reverse-engineering predictions for a neutron star merger wind scenario.

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 score0.009
Threshold uncertainty score0.018

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 head0.050
GPT teacher head0.307
Teacher spread0.257 · 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

Citations72
Published2018
Admission routes3
Has abstractyes

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