Strong coupling from e+e−→hadrons below charm
Bibliographic record
Abstract
We use a new compilation of the hadronic $R$-ratio from available data for the process ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}\text{hadrons}$ to determine the strong coupling, ${\ensuremath{\alpha}}_{s}$. We make use of all data for the $R$-ratio from threshold to a center-of-mass energy of 2 GeV by employing finite-energy sum rules. Data above 2 GeV, for which at present far fewer high-precision experimental data are available, do not provide much additional constraint but are fully consistent with the values for ${\ensuremath{\alpha}}_{s}$ we obtain. Quoting our results at the $\ensuremath{\tau}$ mass to facilitate comparison to the results obtained from analogous analyses of hadronic $\ensuremath{\tau}$-decay data, we find ${\ensuremath{\alpha}}_{s}({m}_{\ensuremath{\tau}}^{2})=0.298\ifmmode\pm\else\textpm\fi{}0.016\ifmmode\pm\else\textpm\fi{}0.006$ in fixed-order perturbation theory, and ${\ensuremath{\alpha}}_{s}({m}_{\ensuremath{\tau}}^{2})=0.304\ifmmode\pm\else\textpm\fi{}0.018\ifmmode\pm\else\textpm\fi{}0.006$ in contour-improved perturbation theory, where the first error is statistical, and the second error reflects our estimate of various systematic effects. These values are in good agreement with a recent determination from the OPAL and ALEPH data for hadronic $\ensuremath{\tau}$ decays.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".