Measurement of jet production cross sections in deep-inelastic ep scattering at HERA
Bibliographic record
Abstract
Abstract A precision measurement of jet cross sections in neutral current deep-inelastic scattering for photon virtualities $$5.5 5.5 < Q 2 < 80 GeV 2 and inelasticities $$0.2 0.2 < y < 0.6 is presented, using data taken with the H1 detector at HERA, corresponding to an integrated luminosity of $$290\,\mathrm {pb}^{-1}$$ 290 pb - 1 . Double-differential inclusive jet, dijet and trijet cross sections are measured simultaneously and are presented as a function of jet transverse momentum observables and as a function of $$Q^2$$ Q 2 . Jet cross sections normalised to the inclusive neutral current DIS cross section in the respective $$Q^2$$ Q 2 -interval are also determined. Previous results of inclusive jet cross sections in the range $$150 150 < Q 2 < 15 , 000 GeV 2 are extended to low transverse jet momenta $$5 5 < P T jet < 7 GeV . The data are compared to predictions from perturbative QCD in next-to-leading order in the strong coupling, in approximate next-to-next-to-leading order and in full next-to-next-to-leading order. Using also the recently published H1 jet data at high values of $$Q^2$$ Q 2 , the strong coupling constant $$\alpha _s(M_Z)$$ α s ( M Z ) is determined in next-to-leading order.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".