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Measurement of Electron-Neutrino Charged-Current Cross Sections on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mmultiscripts><mml:mrow><mml:mi mathvariant="normal">I</mml:mi></mml:mrow><mml:mprescripts/><mml:none/><mml:mrow><mml:mn>127</mml:mn></mml:mrow></mml:mmultiscripts></mml:mrow></mml:math> with the COHERENT <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>NaI</mml:mi><mml:mi>ν</mml:mi><mml:mi mathvariant="normal">E</mml:mi></mml:mrow></mml:math> Detector

2023· article· lv· W4389131213 on OpenAlexaff
P. An, C. Awe, P. S. Barbeau, B. Becker, V. Belov, I. Bernardi, C. Bock, A. Bolozdynya, R. Bouabid, A. Brown, J. Browning, B. Cabrera-Palmer, M. Cervantes, E. Conley, J. Daughhetee, J. Detwiler, K. Ding, M. Durand, Y. Efremenko, S. R. Elliott, L. Fabris, M. Febbraro, A. Gallo Rosso, A. Galindo-Uribarri, A. C. Germer, M. P. Green, J. Hakenmüller, M. R. Heath, S. Hedges, M. Hughes, Bankole A. Johnson, T. Johnson, A. Khromov, A. M. Konovalov, E. Kozlova, A. Kumpan, O. Kyzylova, L. Li, J. M. Link, J. Liu, M. Mahoney, A. Major, Kulwinder Singh Mann, D. M. Markoff, J. Mastroberti, J. Mattingly, P. E. Mueller, J. Newby, D. S. Parno, S. Penttilä, D. Pershey, C. G. Prior, R. Rapp, H. Ray, J. Raybern, O. Razuvaeva, D. Reyna, G. C. Rich, J. Ross, D. Rudik, J. Runge, D. J. Salvat, J. Sander, K. Scholberg, A. Shakirov, G. Simakov, G. Sinev, C. Skuse, W. M. Snow, V. Sosnovtsev, T. Subedi, B. Suh, R. Tayloe, K. Tellez-Giron-Flores, Y.-T. Tsai, E. Ujah, J. Vanderwerp, E. E. van Nieuwenhuizen, R. L. Varner, C.J. Virtue, G. Visser, K. Walkup, Elizabeth Ward, T. Wongjirad, J. Yoo, C.-H. Yu, A. Zawada, J. Zettlemoyer, A. Zderic

Bibliographic record

VenuePhysical Review Letters · 2023
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsLaurentian University
FundersOak Ridge National LaboratoryLawrence Livermore National LaboratoryOffice of ScienceNational Research FoundationAlfred P. Sloan FoundationFermilabLaboratory Directed Research and DevelopmentNational Research Foundation of KoreaU.S. Department of EnergyMinistry of Science and Higher Education of the Russian FederationNational Science Foundation
KeywordsPhysicsNeutrinoSpallation Neutron SourceNeutronNuclear physicsElectronGenerator (circuit theory)Neutron sourceAtomic physics

Abstract

fetched live from OpenAlex

Using an 185-kg NaI[Tl] array, COHERENT has measured the inclusive electron-neutrino charged-current cross section on $^{127}\mathrm{I}$ with pion decay-at-rest neutrinos produced by the Spallation Neutron Source at Oak Ridge National Laboratory. Iodine is one the heaviest targets for which low-energy ($\ensuremath{\le}50\text{ }\text{ }\mathrm{MeV}$) inelastic neutrino-nucleus processes have been measured, and this is the first measurement of its inclusive cross section. After a five-year detector exposure, COHERENT reports a flux-averaged cross section for electron neutrinos of ${9.2}_{\ensuremath{-}1.8}^{+2.1}\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}40}\text{ }\text{ }{\mathrm{cm}}^{2}$. This corresponds to a value that is $\ensuremath{\sim}41%$ lower than predicted using the MARLEY event generator with a measured Gamow-Teller strength distribution. In addition, the observed visible spectrum from charged-current scattering on $^{127}\mathrm{I}$ has been measured between 10 and 55 MeV, and the exclusive zero-neutron and one-or-more-neutron emission cross sections are measured to be ${5.2}_{\ensuremath{-}3.1}^{+3.4}\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}40}$ and ${2.2}_{\ensuremath{-}2.2}^{+3.5}\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}40}\text{ }\text{ }{\mathrm{cm}}^{2}$, respectively.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0010.003
Science and technology studies0.0040.004
Scholarly communication0.0040.003
Open science0.0060.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.2220.007

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 head0.027
GPT teacher head0.272
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

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

Citations18
Published2023
Admission routes1
Has abstractyes

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