Combination and QCD analysis of charm and beauty production cross-section measurements in deep inelastic ep scattering at HERA
Bibliographic record
Abstract
Measurements of open charm and beauty production cross sections in deep inelastic ep scattering at HERA from the H1 and ZEUS Collaborations are combined. Reduced cross sections are obtained in the kinematic range of negative four-momentum transfer squared of the photon $$2.5~\hbox {GeV}^2\le Q^2 \le 2000\, \hbox {GeV}^2$$ and Bjorken scaling variable $$3 \cdot 10^{-5} \le x_\mathrm{Bj} \le 5 \cdot 10^{-2}$$ . The combination method accounts for the correlations of the statistical and systematic uncertainties among the different datasets. Perturbative QCD calculations are compared to the combined data. A next-to-leading order QCD analysis is performed using these data together with the combined inclusive deep inelastic scattering cross sections from HERA. The running charm- and beauty-quark masses are determined as $$m_c(m_c) = 1.290^{+0.046}_{-0.041} \mathrm{(exp/fit)}$$ $${}^{+0.062}_{-0.014} \mathrm{(model)}$$ $${}^{+0.003}_{-0.031} \mathrm{(parameterisation)}$$ GeV and $$m_b(m_b) = 4.049^{+0.104}_{-0.109} \mathrm{(exp/fit)}$$ $${}^{+0.090}_{-0.032} \mathrm{(model)}$$ $${}^{+0.001}_{-0.031} \mathrm{(parameterisation)}~\mathrm{GeV}$$ .
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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 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".