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Studies of neutron-rich nuclei using the CPT mass spectrometer at CARIBU

2011· article· en· W2073331242 on OpenAlexafffundabout
A. Chaudhuri, P. F. Bertone, F. Buchinger, S. Caldwell, J. A. Clark, J. E. Crawford, C. M. Deibel, S. Gulick, D. Lascar, A. F. Levand, G. Li, G. Savard, R. E. Segel, K. S. Sharma, M. Sternberg, T. Sun, J. Van Schelt

Bibliographic record

VenueJournal of Physics Conference Series · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsMcGill UniversityUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsCaliforniumNuclear physicsr-processNeutronPhysicsIsotopeMass spectrometryAtomic physicsNucleosynthesisNuclear reaction

Abstract

fetched live from OpenAlex

The nucleosynthetic path of the astrophysical r-process and the resulting elemental abundances depend on neutron-separation energies which can be determined from the masses of the nuclei along the r-process reaction path. Due to the current lack of experimental data, mass models are often used. The mass values provided by the mass models are often too imprecise or disagree with each other. Therefore, direct high-precision mass measurements of neutron-rich nuclei are necessary to provide input parameters to the calculations and help refine the mass models. The Californium Rare Isotope Breeder Upgrade (CARIBU) facility of Argonne National Laboratory will provide experiments with beams of short-lived neutron-rich nuclei. The Canadian Penning Trap (CPT) mass spectrometer has been relocated to the CARIBU low-energy beam line to extend measurements of the neutron-rich nuclei into the mostly unexplored region along the r-process path. This will allow precise mass measurements (∼ 10 keV/c 2 ) of more than a hundred very neutron-rich isotopes that have not previously been measured.

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)0.002
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 score0.070
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.114
GPT teacher head0.323
Teacher spread0.210 · 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".

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Citations0
Published2011
Admission routes3
Has abstractyes

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