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Record W4380686823 · doi:10.1103/physrevd.107.095043

Effective field theory of chirally enhanced muon mass and dipole operators

2023· article· en· W4380686823 on OpenAlexafffund
Radovan Dermíšek, Keith Hermanek, Navin McGinnis, Sangsik Yoon

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsTRIUMF
FundersNational Research Council CanadaTRIUMFU.S. Department of Energy
KeywordsMuonPhysicsParticle physicsAnomalous magnetic dipole momentDipoleObservablePhysics beyond the Standard ModelHiggs bosonMagnetic dipoleContext (archaeology)Standard Model (mathematical formulation)Electric dipole momentMoment (physics)Effective field theoryNuclear physicsStatistical physicsQuantum mechanics

Abstract

fetched live from OpenAlex

We study corrections to observables related to the muon in the context of models of new physics which generate mass-enhanced corrections to the muon dipole moments. Working in the Standard Model effective theory, we demonstrate a correlation between the decay of the Higgs boson to muons and the magnetic and electric dipole moments of the muon generated by the dominant matching corrections. This defines a novel way to classify predictions for a wide variety of models of new physics based on the pattern of deviations of these three observables. In particular, when applied to specific models, we find that this correlation has a potential to rule out whole models or set upper bounds on the scale of new physics motivated by the muon anomalous magnetic moment.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.393
Teacher spread0.384 · 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 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 routes2
Has abstractyes

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