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Record W7092576518 · doi:10.17181/46a2j-5b415

Searching for dark matter through events with large missing transverse energy recoiling from hadronically decaying vector bosons with the ATLAS detector

2025· article· W7092576518 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Language
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHiggs bosonDark matterLarge Hadron ColliderAtlas (anatomy)BosonStandard Model (mathematical formulation)Parameter spaceDetectorColliderAtlas detector

Abstract

fetched live from OpenAlex

This thesis describes a search for dark matter through the $E_{T}^{miss}$ + V (qq) channel, in which V (qq) is a hadronically decaying W or Z boson, using the full 140 $fb^{−1}$ of 13 TeV centre-of-mass energy proton-proton collisions supplied by the Large Hadron Collider and measured by the ATLAS detector during Run 2 between 2015 and 2018. No significant excesses of events over the expected Standard Model processes are found. Limits are set at the 95% confidence level on the visible cross-section for this channel, and limits on model parameter space are set for the invisible Higgs, simplified s-channel, axion-like-particle, and two Higgs doublet with additional pseudo-scalar models. This work presents the first limits set on the coupling between axion-like-particles and W -bosons, which was found to have a 95% confidence level upper limit of $c_{\bar{W}} < 0.1 at \mathit{f}_{a} = 1 TeV$, and increases linearly with $c_{\bar{W}} /\mathit{f}_{a} = 0.11 TeV^{−1}$.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.011
GPT teacher head0.270
Teacher spread0.258 · 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 designObservational
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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