The azimuthal correlation between the leading jet and the scattered lepton in deep inelastic scattering at HERA
Bibliographic record
Abstract
Abstract The azimuthal correlation angle, $$\Delta \phi $$ Δ ϕ , between the scattered lepton and the leading jet in deep inelastic $$e^{\pm }p$$ e ± p scattering at HERA has been studied using data collected with the ZEUS detector at a centre-of-mass energy of $$\sqrt{s} = 318 {\,\text {Ge}\hspace{-0.66666pt}\text {V}}$$ s = 318 Ge V , corresponding to an integrated luminosity of $$326 \,\text {pb}^{-1}$$ 326 pb - 1 . A measurement of jet cross sections in the laboratory frame was made in a fiducial region corresponding to photon virtuality $$10 {\,\text {Ge}\hspace{-0.66666pt}\text {V}}^2< Q^2 < 350 {\,\text {Ge}\hspace{-0.66666pt}\text {V}}^2$$ 10 Ge V 2 < Q 2 < 350 Ge V 2 , inelasticity $$0.04< y < 0.7$$ 0.04 < y < 0.7 , outgoing lepton energy $$E_e > 10 {\,\text {Ge}\hspace{-0.66666pt}\text {V}}$$ E e > 10 Ge V , lepton polar angle $$140^\circ< \theta _e < 180^\circ $$ 140 ∘ < θ e < 180 ∘ , jet transverse momentum $$2.5 {\,\text {Ge}\hspace{-0.66666pt}\text {V}}< p_\textrm{T,jet} < 30 {\,\text {Ge}\hspace{-0.66666pt}\text {V}}$$ 2.5 Ge V < p T,jet < 30 Ge V , and jet pseudorapidity $$-1.5< \eta _\textrm{jet} < 1.8$$ - 1.5 < η jet < 1.8 . Jets were reconstructed using the $$k_\textrm{T}$$ k T algorithm with the radius parameter $$R = 1$$ R = 1 . The leading jet in an event is defined as the jet that carries the highest $$p_\textrm{T,jet}$$
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".