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Prompt photons with associated jets in photoproduction at HERA

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S. Chekanov (for the ZEUS Collaboration)

High Energy Physics - Experiment · Submitted 18 May 2007

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Predictions based on leading-logarithm parton-shower Monte Carlo models and next-to-leading-order (NLO) QCD underestimate the gamma+jet cross sections for transverse energies of prompt photons below 7 GeV, while the kT-factorisation QCD calculation agrees with the data in this region.

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arXiv ID0705.2700 (version 1)
Pith IDCLDYUE7U, Pith's permanent record of this paper and its review
CitationS. Chekanov (for the ZEUS Collaboration). "Prompt photons with associated jets in photoproduction at HERA." arXiv:0705.2700 (2007). https://pith.science/paper/CLDYUE7U
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,378 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.17 · human participants 0.02 · controlled comparison 0.12 · randomized assignment 0.01 · states quantitative result 0.87 · compares with prior results 0.90 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

Prompt photons, together with an accompanying jet, have been studied in the photoproduction regime of ep scattering with the ZEUS detector at HERA. Predictions based on leading-logarithm parton-shower Monte Carlo models and next-to-leading-order (NLO) QCD underestimate the gamma+jet cross sections for transverse energies of prompt photons below 7 GeV, while the kT-factorisation QCD calculation agrees with the data in this region.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Prompt photons, together with an accompanying jet, have been studied in the photoproduction regime of ep scattering with the ZEUS detector at HERA. contribution 0.86 0.87 0.04 asserted 0.98
s1 Predictions based on leading-logarithm parton-shower Monte Carlo models and next-to-leading-order (NLO) QCD underestimate the gamma+jet cross sections for transverse energies of prompt photons below 7 GeV, while the kT-factorisation QCD calculation agrees with the data in this region. result 0.98 0.66 0.70 asserted 1.00

What kind of paper the classifier reports this is: empirical study 1.00 · evidence from observation or experiment 0.88.

What was examined, and what was not

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  • references and citing sentences
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  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Prompt photons, together with an accompanying jet, have been studied in the photoproduction regime of ep scattering with the ZEUS detector at HERA. Predictions based on leading-logarithm parton-shower Monte Carlo models and next-to-leading-order (NLO) QCD underestimate the gamma+jet cross sections for transverse energies of prompt photons below 7 GeV, while the kT-factorisation QCD calculation agrees with the data in this region.

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2 arXiv papers cite this in 2 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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