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Record W222625658 · doi:10.1051/epjconf/20122812020

A search for ${\rm{t\bar t}}$ resonances in the dilepton channel in 1.04 fb<sup>−1</sup>of pp collisions at<i>√s</i>= 7 TeV with the ATLAS detector

2012· article· en· W222625658 on OpenAlexaff

Bibliographic record

VenueEPJ Web of Conferences · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of British ColumbiaTRIUMF
Fundersnot available
KeywordsLarge Hadron ColliderBosonStandard Model (mathematical formulation)MuonCompact Muon SolenoidAtlas (anatomy)Branching fractionATLAS experimentResonance (particle physics)

Abstract

fetched live from OpenAlex

The first ATLAS result on a search for a high mass top pair resonance at the LHC in the subset of events where both W bosons from the top decays decay to either a final state electron or muon is presented. The analysis is performed on 1.04 fb−1 of pp collisions at √s = 7 TeV. Numerous models predict the production of new massive particles that decay preferentially to a top-anti-top pair, including Randall-Sundrum models where the observation of a Kaluza-Klein excitation of the gluon may be the first indication of the existence of an extra spatial dimension. In the analysis presented, a simple observable, sensitive to resonance mass, is formed by summing the missing transverse energy, and the transverse momenta of the selected jets and the two candidate leptons. A deviation from the Standard Model prediction for this observable is searched for using Bayesian statistical methods that compare the yields, and shapes, of the Standard Model background and signal predictions for KK-gluons with masses between 500 and 1600 GeV. No excess over the Standard Model is observed and 95% C.L. upper limits are set on the production cross-section times branching ratio to top quarks for KK-gluon-like resonances. The results of the analysis exclude Randall-Sundrum KK-gluons with masses less than 840 GeV.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.277

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 head0.026
GPT teacher head0.280
Teacher spread0.253 · 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 designBench or experimental
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
Published2012
Admission routes1
Has abstractyes

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