Erratum to: Determination of the strong coupling constant $${{\varvec{\alpha _{\mathrm{s}} (m_{\mathrm{Z}})}}}$$ in next-to-next-to-leading order QCD using H1 jet cross section measurements
Bibliographic record
Abstract
Abstract The determination of the strong coupling constant $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}})$$ α s ( m Z ) from H1 inclusive and dijet cross section data [1] exploits perturbative QCD predictions in next-to-next-to-leading order (NNLO) [2–4]. An implementation error in the NNLO predictions was found [4] which changes the numerical values of the predictions and the resulting values of the fits. Using the corrected NNLO predictions together with inclusive jet and dijet data, the strong coupling constant is determined to be $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}}) =0.1166\,(19)_{\mathrm{exp}}\,(24)_{\mathrm{th}}$$ α s ( m Z ) = 0.1166 ( 19 ) exp ( 24 ) th . Complementarily, $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}})$$ α s ( m Z ) is determined together with parton distribution functions of the proton (PDFs) from jet and inclusive DIS data measured by the H1 experiment. The value $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}}) =0.1147\,(25)_{\mathrm{tot}}$$ α s ( m Z ) = 0.1147 ( 25 ) tot obtained is consistent with the determination from jet data alone. Corrected figures and numerical results are provided and the discussion is adapted accordingly.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.024 |
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".