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Record W4407309053 · doi:10.48550/arxiv.2502.04634

The generic basis and flavour non-universal SMEFT

2025· preprint· en· W4407309053 on OpenAlexfundno aff
Alakabha Datta, Jean-François Fortin, Jacky Kumar, David London, Danny Marfatia, Nicolas Sanfaçon

Bibliographic record

VenuearXiv (Cornell University) · 2025
Typepreprint
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesLos Alamos National LaboratoryNational Nuclear Security AdministrationNatural Sciences and Engineering Research Council of CanadaLaboratory Directed Research and DevelopmentU.S. Department of EnergyNational Science Foundation
KeywordsComputer science

Abstract

fetched live from OpenAlex

Whenever an anomaly in the flavour sector appears, analyses are performed examining whether it can be explained by adding a small number of carefully-chosen flavour non-universal four-fermion SMEFT operators. These analyses are typically carried out in the down or the up basis, i.e., it is assumed that the weak and mass eigenstates are the same for the left-handed down-type or up-type quarks. In these bases, there is no dependence on the matrices that transform from the weak to the mass basis, and which are unmeasurable in the Standard Model. In this paper, we argue that it is better to use a generic weak basis, in which no assumptions about the alignment of weak and mass eigenstates are made. The analysis now directly includes elements of the transformation matrices. By doing a fit to the data, it is possible to both determine if the flavour anomaly can be explained and extract the transformation matrices. In principle, this can be extended to a complete reconstruction of the Yukawa matrices.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.666
Threshold uncertainty score0.975

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 science0.0000.000
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 head0.029
GPT teacher head0.156
Teacher spread0.127 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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