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Record W3042028636 · doi:10.1007/jhep06(2019)142

A μ-τ-philic scalar doublet under Zn flavor symmetry

2019· article· en· W3042028636 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of High Energy Physics · 2019
Typearticle
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsMcGill University
FundersJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of CanadaMinistry of Education, Culture, Sports, Science and Technology
KeywordsLeptonMuonAnomalous magnetic dipole momentElectroweak interactionScalar (mathematics)Parameter spaceDiscrete symmetryHiggs bosonPhysics beyond the Standard Model

Abstract

fetched live from OpenAlex

A bstract We propose a minimal model which accommodates the long-standing anomaly of muon magnetic moment based on abelian discrete flavor symmetries. The standard model is extended by scalar doublets charged under a Z n lepton flavor symmetry. In these models, a large contribution to the muon magnetic moment can be obtained by the chirality enhancement from new scalar mediated diagrams without conflicting with the flavor symmetry. Thanks to the lepton flavor symmetry, these models automatically forbid lepton flavor violation. The minimal model is based on Z 4 symmetry with only one extra scalar doublet. In this model, we show that the parameter space favored by the muon g − 2 can easily be consistent with experimental constraints and theoretical bounds such as the electroweak precision tests, lepton universality, potential stability condition and triviality bound as well as the LHC direct search mass bound. The new contributions to the muon electric dipole moment and the Higgs decay into γγ can be indirect signals of the model.

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.

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 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: none
Teacher disagreement score0.922
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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