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Record W3013108620 · doi:10.1051/epjconf/201921909001

Measurement of the angular distribution of γ-rays after neutron capture by <sup>139</sup>La for a T-violation search

2019· article· en· W3013108620 on OpenAlexaff
Takuya Okudaira, Hirohiko M. Shimizu, Masaaki Kitaguchi, K. Hirota, C. Haddock, I. Ito, Tomoki Yamamoto, Shunsuke Endo, Kohei Ishizaki, Takumi Sato, Shusuke Takada, Jun Koga, T. Yoshioka, Takashi Ino, Kouichiro Asahi, Takamasa Momose, Takahiro Iwata, Takayuki Oku, K. Sakai, A. Kimura, T. Nakao, Masanori Hino, Tatsushi Shima, Yutaka Yamagata

Bibliographic record

VenueEPJ Web of Conferences · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhysicsNeutronNuclear physicsProtonNuclear reactionPolarizerAmplitudeNeutron captureAtomic physicsOptics

Abstract

fetched live from OpenAlex

Parity violating effects enhanced by up to 106 times compared to proton-proton scattering have been observed in several neutron capture induced compound nuclei. This enhancement is explained as an interference between an s-wave and a p-wave amplitude (s-p mixing). Theory predicts that this mechanism can also enhance T-violating effects. For estimation of this enhancement in a promising candidate nucleus, we measured the angular distribution of γ-rays in the (n,γ) reaction induced in a 139La target. Experiments were performed at J-PARC, using a germanium detector array at an intense neutron beam. Analysis of the observed angular dependence around the 0.74 eV p-wave resonance allowed us to determine the ratio of the partial p-wave neutron width to the total neutron width in the entrance channel of the compound nucleus. We also report our development of a 3He spin filter needed as an epithermal-neutron polarizer for the T-violation search.

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 score0.003
Threshold uncertainty score0.011

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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