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Record W4389298315 · doi:10.1103/physrevd.108.115001

Scotogenic explanation for the 95 GeV excesses

2023· article· en· W4389298315 on OpenAlexfundno aff
Pablo Escribano, Víctor Martín Lozano, Avelino Vicente

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersMinisterio de Economía y CompetitividadAgencia Estatal de InvestigaciónGeneralitat ValencianaFPInnovationsMinisterio de UniversidadesEuropean Commission
KeywordsPhysicsParticle physicsElectroweak interactionSigmaHiggs bosonLarge Hadron ColliderNeutrinoMAJORANAPhysics beyond the Standard ModelDark matterColliderInvariant massQuantum mechanics

Abstract

fetched live from OpenAlex

Several hints of the presence of a new state at about 95 GeV have been observed recently. The CMS and ATLAS Collaborations have reported excesses in the diphoton channel at about this diphoton invariant mass with local statistical significances of $2.9\ensuremath{\sigma}$ and $1.7\ensuremath{\sigma}$, respectively. Furthermore, a $2\ensuremath{\sigma}$ excess in the $b\overline{b}$ final state was also observed at LEP, again pointing at a similar mass value. We interpret these intriguing hints of new physics in a variant of the Scotogenic model, an economical scenario that induces Majorana neutrino masses at the loop level and includes a viable dark matter candidate. We show that our model can explain the 95 GeV excesses while respecting the relevant collider, Higgs, and electroweak precision bounds and discuss other phenomenological features of our scenario.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.030
GPT teacher head0.449
Teacher spread0.419 · 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

Citations26
Published2023
Admission routes1
Has abstractyes

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