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Record W6950672682 · doi:10.5445/ir/1000089226

Measurement of the differential cross sections for W -boson production in association with jets in p$\bar{p}$ collisions at √s =1.96 TeV

2018· article· en· W6950672682 on OpenAlexfundno aff

Bibliographic record

VenueRepository KITopen (Karlsruhe Institute of Technology) · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersFermilabIstituto Nazionale di Fisica NucleareAustralian Research CouncilNational Research Foundation of KoreaMinisterio de Ciencia e InnovaciónBundesministerium für Bildung und ForschungRussian Foundation for Basic ResearchAcademy of FinlandNatural Sciences and Engineering Research Council of CanadaAlfred P. Sloan FoundationNational Science CouncilMinistry of Education, Culture, Sports, Science and TechnologyScience and Technology Facilities CouncilNational Research FoundationNational Science FoundationRoyal SocietySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungU.S. Department of Energy
KeywordsLeptonCollider Detector at FermilabFermilabCross section (physics)ColliderLuminosityScattering cross-sectionJet (fluid)BosonDetector

Abstract

fetched live from OpenAlex

This paper presents a study of the production of a single W boson in association with one or more jets in proton-antiproton collisions at √s=1.96 TeV, using the entire data set collected in 2001–2011 by the Collider Detector at Fermilab at the Tevatron, which corresponds to an integrated luminosity of 9.0 fb−1. The W boson is identified through its leptonic decays into electron and muon. The production cross sections are measured for each leptonic decay mode and combined after testing that the ratio of the W(→μν)+jets cross section to the W(→eν)+jets cross section agrees with the hypothesis of e-μ lepton universality. The combination of measured cross sections, differential in the inclusive jet multiplicity (W+≥N jets with N=1, 2, 3, or 4) and in the transverse energy of the leading jet, are compared with theoretical predictions.

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 score0.675
Threshold uncertainty score0.339

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 head0.014
GPT teacher head0.264
Teacher spread0.251 · 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
Published2018
Admission routes1
Has abstractyes

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