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Record W6901659668 · doi:10.60692/cwmzk-4pb76

Measurement of the transverse momentum and $$\phi ^*_{\eta }$$ ϕ η ∗ distributions of Drell–Yan lepton pairs in proton–proton collisions at $$\sqrt{s}=8$$ s = 8 TeV with the ATLAS detector

2016· article· en· W6901659668 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversité de MontréalInstitute of Particle PhysicsUniversity of VictoriaUniversity of Toronto
Fundersnot available
KeywordsMonte Carlo methodLeptonRapidityAtlas (anatomy)DetectorLarge Hadron ColliderTransverse planeRange (aeronautics)

Abstract

fetched live from OpenAlex

Distributions of transverse momentum $$p_T^{\ell \ell }$$ and the related angular variable $$\phi ^*_\eta $$ of Drell–Yan lepton pairs are measured in 20.3 fb $$^{-1}$$ of proton–proton collisions at $$\sqrt{s}=8$$ TeV with the ATLAS detector at the LHC. Measurements in electron-pair and muon-pair final states are corrected for detector effects and combined. Compared to previous measurements in proton–proton collisions at $$\sqrt{s}=7$$ TeV, these new measurements benefit from a larger data sample and improved control of systematic uncertainties. Measurements are performed in bins of lepton-pair mass above, around and below the Z-boson mass peak. The data are compared to predictions from perturbative and resummed QCD calculations. For values of $$\phi ^*_\eta < 1$$ the predictions from the Monte Carlo generator ResBos are generally consistent with the data within the theoretical uncertainties. However, at larger values of $$\phi ^*_\eta $$ this is not the case. Monte Carlo generators based on the parton-shower approach are unable to describe the data over the full range of $$p_T^{\ell \ell }$$ while the fixed-order prediction of Dynnlo falls below the data at high values of $$p_T^{\ell \ell }$$ . ResBos and the parton-shower Monte Carlo generators provide a much better description of the evolution of the $$\phi ^*_\eta $$ and $$p_T^{\ell \ell }$$ distributions as a function of lepton-pair mass and rapidity than the basic shape of the data.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.197
Teacher spread0.180 · 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 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
Published2016
Admission routes1
Has abstractyes

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