Data-based determination of the isospin-limit light-quark-connected contribution to the anomalous magnetic moment of the muon
Bibliographic record
Abstract
We describe how recent determinations of exclusive-mode contributions to ${a}_{\ensuremath{\mu}}^{\mathrm{LO},\mathrm{HVP}}$, the leading-order hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon, can be used to provide, up to small electromagnetic (EM) corrections accessible from the lattice, a data-based dispersive determination of ${a}_{\ensuremath{\mu}}^{\text{lqc};\mathrm{IL}}$, the isospin-limit, light-quark-connected contribution to ${a}_{\ensuremath{\mu}}^{\mathrm{LO},\mathrm{HVP}}$. Such a determination is of interest in view of the existence of a number of lattice results for this quantity, emerging evidence for a tension between lattice and dispersive determinations of ${a}_{\ensuremath{\mu}}^{\mathrm{LO},\mathrm{HVP}}$, and the desire to clarify the source of this tension. Taking as input for the small EM correction that must be applied to the purely data-driven dispersive determination the result $\ensuremath{-}0.93(58)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}10}$ obtained in a recent BMW lattice study, we find ${a}_{\ensuremath{\mu}}^{\text{lqc};\mathrm{IL}}$ to be $635.0(2.7)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}10}$ if the results of Keshavarzi, Nomura, and Teubner are used for the exclusive-mode contributions and $638.4(4.1)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}10}$ if instead those of Davier, H\"ocker, Malaescu, and Zhang are used.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".