Measurement of subjet multiplicities in neutral current deep inelastic scattering at HERA and determination of αs
Bibliographic record
Abstract
The subjet multiplicity has been measured in neutral current e+p interactions at Q2>125 GeV2 with the ZEUS detector at HERA using an integrated luminosity of 38.6 pb−1. Jets were identified in the laboratory frame using the longitudinally invariant kT cluster algorithm. The number of jet-like substructures within jets, known as the subjet multiplicity, is defined as the number of clusters resolved in a jet by reapplying the jet algorithm at a smaller resolution scale ycut. Measurements of the mean subjet multiplicity, 〈nsbj〉, for jets with transverse energies ET,jet>15 GeV are presented. Next-to-leading-order perturbative QCD calculations describe the measurements well. The value of αs(MZ), determined from 〈nsbj〉 at ycut=10−2 for jets with 25<ET,jet<71 GeV, is αs(MZ)=0.1187±0.0017(stat.)+0.0024−0.0009(syst.)+0.0093−0.0076(th.).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".