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Record W7030099492

Measurement of the inclusive cross section of p°, fâ(980) and fâ(1270) mesons in deep inelastic scattering at HERA

2005· other· en· W7030099492 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2005
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDESYHERAMesonDeep inelastic scatteringCross section (physics)ZEUS (particle detector)LuminosityScatteringInelastic scattering
DOInot available

Abstract

fetched live from OpenAlex

The production of neutral meson resonances in deep inelastic scattering has been studied in DESY with the ZEUS detector at the HERA collider. The rho 0, f0(980) and f2(1270) total cross sections, as well as differential pT and eta cross sections, were measured in the 0 GeV < pT < 7 GeV and |eta| < 1 ranges. The obtained total cross sections were sr0 = 19.21 +/- 0.92 (stat.) +/- 7.59 (syst.) nb, sf0 = 0.63 +/- 0.04 (stat.) +/- 0.25 (syst.) nb and sf2 = 3.62 +/- 0.02 (stat.) +/- 1.73 (syst.) nb. The cross sections measurements for f0 and f2 mesons are underestimated since acceptances had to be overestimated. The measurements were performed on a data sample with 82.5 nb-1 of integrated luminosity and for a squared momentum transfer greater than 3 GeV2 .

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.004
GPT teacher head0.159
Teacher spread0.156 · 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
Published2005
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)→French-language works237,207→