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Record W2084402072 · doi:10.1103/physrevd.90.115014

Leptophobic dark matter at neutrino factories

2014· article· en· W2084402072 on OpenAlexafffund
Brian Batell, Patrick deNiverville, David McKeen, Maxim Pospelov, Adam Ritz

Bibliographic record

VenuePhysical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsPerimeter InstituteUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaMedtronicU.S. Department of EnergyNational Science Foundation
KeywordsPhysicsMiniBooNEParticle physicsDark matterNeutrinoBaryonBaryon numberStandard Model (mathematical formulation)Sensitivity (control systems)LuminosityNuclear physicsPhysics beyond the Standard ModelWarm dark matterSterile neutrinoHot dark matterCosmologyAstrophysicsDark energyNeutrino oscillationGalaxy

Abstract

fetched live from OpenAlex

High-luminosity fixed-target neutrino experiments present a new opportunity to search for light sub-GeV dark matter and associated new forces. We analyze the physics reach of these experiments to light leptophobic dark states coupled to the Standard Model via gauging the $U(1{)}_{B}$ baryon current. When the baryonic vector is light, and can decay to dark matter, we find that the MiniBooNE experiment in its current beam-dump configuration can extend sensitivity to the baryonic fine structure constant down to ${\ensuremath{\alpha}}_{B}\ensuremath{\sim}{10}^{\ensuremath{-}6}$. This is significantly below the existing limits over much of the sub-GeV mass range currently inaccessible to direct detection experiments.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.483
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.301
Teacher spread0.286 · 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

Citations107
Published2014
Admission routes2
Has abstractyes

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