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Record W6977067297 · doi:10.60692/kf6nk-tbs13

Measurement of the underlying event in jet events from 7 $$\text {TeV}$$ TeV proton–proton collisions with the ATLAS detector

2014· article· en· W6977067297 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicWar, Ethics, and Justification
Canadian institutionsUniversité de MontréalInstitute of Particle PhysicsUniversity of VictoriaUniversity of Toronto
Fundersnot available
KeywordsMonte Carlo methodRapidityEvent (particle physics)Multiplicity (mathematics)Large Hadron ColliderObservableTransverse planeQuantum chromodynamics

Abstract

fetched live from OpenAlex

Distributions sensitive to the underlying event in QCD jet events have been measured with the ATLAS detector at the LHC, based on $$37~\text {pb}^{-1}$$ of proton–proton collision data collected at a centre-of-mass energy of 7 $$\text {TeV}$$ . Charged-particle mean $$p_{\mathrm {T}}$$ and densities of all-particle $$E_{\mathrm {T}}$$ and charged-particle multiplicity and $$p_{\mathrm {T}}$$ have been measured in regions azimuthally transverse to the hardest jet in each event. These are presented both as one-dimensional distributions and with their mean values as functions of the leading-jet transverse momentum from 20 to 800 $$\text {GeV}$$ . The correlation of charged-particle mean $$p_{\mathrm {T}}$$ with charged-particle multiplicity is also studied, and the $$E_{\mathrm {T}}$$ densities include the forward rapidity region; these features provide extra data constraints for Monte Carlo modelling of colour reconnection and beam-remnant effects respectively. For the first time, underlying event observables have been computed separately for inclusive jet and exclusive dijet event selections, allowing more detailed study of the interplay of multiple partonic scattering and QCD radiation contributions to the underlying event. Comparisons to the predictions of different Monte Carlo models show a need for further model tuning, but the standard approach is found to generally reproduce the features of the underlying event in both types of event selection.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.103
GPT teacher head0.236
Teacher spread0.133 · 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 designQualitative
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
Published2014
Admission routes1
Has abstractyes

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