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Record W6996884769

Substructure dependence of jet cross sections at HERA and determination of #alpha#_s

2004· article· en· W6996884769 on OpenAlexfundno aff

Bibliographic record

VenueDIAL (Catholic University of Leuven) · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersHigh Energy PhysicsDeutsches Elektronen-SynchrotronNatural Sciences and Engineering Research Council of CanadaLomonosov Moscow State UniversityNuclear PhysicsStrongBundesministerium für Bildung und ForschungMinistry of Education, Culture, Sports, Science and TechnologyUniversity of Oxford
KeywordsHERASubstructurePartonJet (fluid)Multiplicity (mathematics)ZEUS (particle detector)Deep inelastic scatteringScattering
DOInot available

Abstract

fetched live from OpenAlex

Jet substructure and differential cross sections for jets produced in the\nphotoproduction and deep inelastic ep scattering regimes have been measured\nwith the ZEUS detector at HERA using an integrated luminosity of 82.2 pb-1. The\nsubstructure of jets has been studied in terms of the jet shape and subjet\nmultiplicity for jets with transverse energies Et(jet) > 17 GeV. The data are\nwell described by the QCD calculations. The jet shape and subjet multiplicity\nare used to tag gluon- and quark-initiated jets. Jet cross sections as\nfunctions of Et(jet), jet pseudorapidity, the jet-jet scattering angle, dijet\ninvariant mass and the fraction of the photon energy carried by the dijet\nsystem are presented for gluon- and quark-tagged jets. The data exhibit the\nbehaviour expected from the underlying parton dynamics. A value of alphas(Mz)\nof alphas(Mz) = 0.1176 +-0.0009(stat.) -0.0026 +0.0009 (exp.) -0.0072 +0.0091\n(th.) was extracted from the measurements of jet shapes in deep inelastic\nscattering.\n Comment: 67 pages, 17 figures, 24 tables

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.255

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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

Citations1
Published2004
Admission routes1
Has abstractyes

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