ZEUS next-to-leading-order QCD analysis of data on deep inelastic scattering
Bibliographic record
Abstract
Next-to-leading-order QCD analyses of the ZEUS data on deep inelastic scattering together with fixed-target data have been performed, from which the gluon and quark densities of the proton and the value of the strong coupling constant ${\ensuremath{\alpha}}_{s}{(M}_{Z})$ were extracted. The study includes a full treatment of the experimental systematic uncertainties including point-to-point correlations. The resulting uncertainties in the parton density functions are presented. A combined fit for ${\ensuremath{\alpha}}_{s}{(M}_{Z})$ and the gluon and quark densities yields a value for ${\ensuremath{\alpha}}_{s}{(M}_{Z})$ in agreement with the world average. The parton density functions derived from ZEUS data alone indicate the importance of HERA data in determining the sea quark and gluon distributions at low x. The limits of applicability of the theoretical formalism have been explored by comparing the fit predictions to ZEUS data at very low ${Q}^{2}.$
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".