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Record W2725966095 · doi:10.1103/physrevc.96.042501

First direct constraints on Fierz interference in free-neutron <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>β</mml:mi></mml:math> decay

2017· article· en· W2725966095 on OpenAlexaff
K. P. Hickerson, X. Sun, Yelena Bagdasarova, D. Bravo, L. J. Broussard, Michael Brown, R. Carr, S. Currie, Xuefeng Ding, B. W. Filippone, A. Garcı́a, P. Geltenbort, J. Hoagland, A. T. Holley, R. Hong, T. M. Ito, A. Knecht, C.-Y. Liu, J. L. Liu, M. Makela, R. Mammei, Jean Martin, D. Melconian, M. P. Mendenhall, S. D. Moore, C. L. Morris, R. W. Pattie, A. Pérez Galván, R. Picker, M. L. Pitt, B. Plaster, J. Ramsey, R. R. Rios, A. Saunders, S. J. Seestrom, E. I. Sharapov, W. E. Sondheim, E. Tatar, R. B. Vogelaar, B. VornDick, C. Wrede, A. R. Young, B. A. Zeck

Bibliographic record

VenuePhysical review. C · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsTRIUMFUniversity of Winnipeg
FundersLos Alamos National LaboratoryLaboratory Directed Research and DevelopmentNuclear PhysicsU.S. Department of EnergyNational Science Foundation
KeywordsPhysicsMathematicsComputer science

Abstract

fetched live from OpenAlex

Precision measurements of free-neutron $\ensuremath{\beta}$ decay have been used to precisely constrain our understanding of the weak interaction. However, the neutron Fierz interference term ${b}_{n}$, which is particularly sensitive to beyond-standard-model tensor currents at the TeV scale, has thus far eluded measurement. Here we report the first direct constraints on this term, finding ${b}_{n}=0.067\ifmmode\pm\else\textpm\fi{}0.{005}_{\text{stat}}{}_{\ensuremath{-}0.061}^{+0.090}{}_{\text{sys}}$, consistent with the standard model. The uncertainty is dominated by absolute energy reconstruction and the linearity of the $\ensuremath{\beta}$ spectrometer energy response.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score1.000

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 science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.031
GPT teacher head0.316
Teacher spread0.285 · 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.

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

Citations21
Published2017
Admission routes1
Has abstractyes

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