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Record W1988439317 · doi:10.1007/jhep04(2010)116

Lepton jets in (supersymmetric) electroweak processes

2010· article· en· W1988439317 on OpenAlexaff
Clifford Cheung, Joshua T. Ruderman, Lian-Tao Wang, Itay Yavin

Bibliographic record

VenueJournal of High Energy Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsInstitute of Particle Physics
FundersU.S. Department of EnergyNational Science Foundation
KeywordsPhysicsParticle physicsLeptonElectroweak interactionDark matterLarge Hadron ColliderTevatronElectroweak scalePhenomenology (philosophy)TechnicolorBosonPhysics beyond the Standard ModelNuclear physicsGauge bosonGauge theory

Abstract

fetched live from OpenAlex

We consider some of the recent proposals in which weak-scale dark matter is accompanied by a GeV scale dark sector that could produce spectacular lepton-rich events at the LHC. Since much of the collider phenomenology is only weakly model dependent it is possible to arrive at generic predictions for the discovery potential of future experimental searches. We concentrate on the production of dark states through Z 0 bosons and electroweak-inos at the Tevatron or LHC, which are the cleanest channels for probing the dark sector. We properly take into account the effects of dark radiation and dark cascades on the formation of lepton jets. Finally, we present a concrete definition of a lepton jet and suggest several approaches for inclusive experimental searches.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.001
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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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 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

Citations87
Published2010
Admission routes1
Has abstractyes

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