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Record W4360595266 · doi:10.1051/epjconf/202327911006

Indirect measurements of neutron-induced reaction cross sections at storage rings

2023· article· en· W4360595266 on OpenAlexaff
M. Sguazzin, B. Jurado, J. Pibernat, J. A. Swartz, M. Grieser, J. Glorius, Yu. A. Litvinov, R. Reifarth, K. Blaum, P. Alfaurt, P. Ascher, L. Audouin, C. Berthelot, Β. Blank, B. Bruckner, S. Dellmann, I. Dillmann, C. Domingo‐Pardo, Marc Dupuis, P. Erbacher, M. Flayol, O. Forstner, D. Freire-Fernández, M. Gerbaux, J. Giovinazzo, S. Grévy, C. J. Griffin, A. Gumberidze, S. Heil, A. Heinz, D. Kurtulgil, G. Leckenby, S. Litvinov, B. Lorentz, V. Méot, J. Michaud, S. Pérard, N. Petridis, U. Popp, D. Ramos, M. Roche, M. S. Sanjari, R. S. Sidhu, U. Spillmann, M. Steck, Th. Stöhlker, B. Thomas, L. Thulliez, M. Versteegen

Bibliographic record

VenueEPJ Web of Conferences · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsTRIUMF
FundersInstitut National de Physique Nucléaire et de Physique des ParticulesKnut och Alice Wallenbergs StiftelseCentre National de la Recherche ScientifiqueEuropean Commission
KeywordsStorage ringHeavy ionNuclear physicsPhysicsNeutronRing (chemistry)Inverse kinematicsNuclear reactionNuclear engineeringKinematicsIonChemistryEngineeringOpticsClassical mechanicsOrganic chemistry

Abstract

fetched live from OpenAlex

Neutron-induced reaction cross sections of unstable nuclei are essential for understanding the synthesis of heavy elements in stars. However, their measurement is very difficult due to the radioactivity of the targets involved. We propose to circumvent this problem by using for the first time the surrogate reaction method in inverse kinematics at heavy-ion storage rings. In this contribution, we describe the developments we have done to perform surrogate-reaction studies at the storage rings of GSI/FAIR. In particular, we present the first results of the proof of principle experiment, which we conducted recently at the Experimental Storage Ring (ESR).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.399

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 head0.090
GPT teacher head0.342
Teacher spread0.251 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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