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Simultaneous Measurement of Muon Neutrino <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>ν</mml:mi><mml:mi>μ</mml:mi></mml:msub></mml:math> Charged-Current Single <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mi>π</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:math> Production in CH, C, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">H</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math>, Fe, and Pb Targets in MINERvA

2023· article· lv· W4296413558 on OpenAlexaff
A. Bercellie, K. A. Kroma-Wiley, S. Akhter, Z. Ahmad Dar, F. Akbar, V. Ansari, M. V. Ascencio, M. Sajjad Athar, L. Bellantoni, M. Betancourt, A. Bodek, J. L. Bonilla, A. Bravar, H. Budd, G. Caceres, T. Cai, G. A. Díaz, H. da Motta, S. Dytman, J. Félix, L. Fields, A. Filkins, R. Fine, A. M. Gago, H. Gallagher, P. K. Gaur, S. M. Gilligan, R. Gran, E. Granados, D. A. Harris, C. Jena, S. Jena, J. Kleykamp, A. Klustová, M. Kordosky, D. Last, Thanh Cao Le, A. Lozano, X. -G. Lu, I. Mahbub, E. Maher, S. Manly, W. A. Mann, C. Mauger, K. S. McFarland, B. Messerly, J. Miller, O. Moreno, J. G. Morfín, D. Naples, J. K. Nelson, C. Nguyen, A. Olivier, V. Paolone, G. N. Perdue, Komninos-John Plows, M. A. Ramírez, R. D. Ransome, H. Ray, D. Ruterbories, H. Schellman, C. J. Solano Salinas, H. Su, M. Sultana, V. S. Syrotenko, B. Utt, E. Valencia, N. H. Vaughan, A. V. Waldron, B. Yaeggy, L. Zazueta

Bibliographic record

VenuePhysical Review Letters · 2023
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsYork University
FundersFondo Nacional de Desarrollo Científico y TecnológicoFermilabHigh Energy PhysicsComisión Nacional de Investigación Científica y TecnológicaVicerrectoría de Investigación, Desarrollo e InnovaciónOffice of ScienceAgencia Nacional de Investigación y DesarrolloAsociación para el Estudio y Apoyo a las FamiliasConsejo Nacional de Ciencia, Tecnología e Innovación TecnológicaResearch Corporation for Scientific AdvancementNarodowe Centrum NaukiH2020 Marie Skłodowska-Curie ActionsDirección de Gestión de la Investigación, Universidad de AntofagastaConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorScience and Technology Facilities CouncilUniversity of RochesterU.S. Department of EnergyPontificia Universidad Católica del PerúNational Science FoundationImperial College LondonConsejo Nacional de Ciencia y Tecnología
KeywordsPhysicsCharged currentNeutrinoMuonNuclear physicsNucleonParticle physicsMuon neutrinoNeutrino oscillationLeptonCurrent (fluid)Production (economics)Oscillation (cell signaling)Coupling (piping)Neutral currentNeutrino detectorElectronChemistry

Abstract

fetched live from OpenAlex

Neutrino-induced charged-current single ${\ensuremath{\pi}}^{+}$ production in the $\mathrm{\ensuremath{\Delta}}(1232)$ resonance region is of considerable interest to accelerator-based neutrino oscillation experiments. In this Letter, high statistic differential cross sections are reported for the semiexclusive reaction ${\ensuremath{\nu}}_{\ensuremath{\mu}}A\ensuremath{\rightarrow}{\ensuremath{\mu}}^{\ensuremath{-}}{\ensuremath{\pi}}^{+}+$ nucleon(s) on scintillator, carbon, water, iron, and lead targets recorded by MINERvA using a wideband ${\ensuremath{\nu}}_{\ensuremath{\mu}}$ beam with $⟨{E}_{\ensuremath{\nu}}⟩\ensuremath{\approx}6\text{ }\text{ }\mathrm{GeV}$. Suppression of the cross section at low ${Q}^{2}$ and enhancement of low ${T}_{\ensuremath{\pi}}$ are observed in both light and heavy nuclear targets compared with phenomenological models used in current neutrino interaction generators. The cross sections per nucleon for iron and lead compared with CH across the kinematic variables probed are 0.8 and 0.5 respectively, a scaling which is also not predicted by current generators.

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)0.006
metaresearch head score (Gemma)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0030.006
Meta-epidemiology (broad)0.0020.006
Bibliometrics0.0020.005
Science and technology studies0.0040.005
Scholarly communication0.0040.005
Open science0.0060.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0840.007

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 head0.023
GPT teacher head0.259
Teacher spread0.236 · 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 designTheoretical or conceptual
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

Citations8
Published2023
Admission routes1
Has abstractyes

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