Experimental input from $e^+e^-$ machines to hadronic contribution to muon (g-2)
Bibliographic record
Abstract
Precise study of the hadrons production in \bm{e^+e^-} <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mstyle mathvariant="bold"> <mml:msup> <mml:mi>𝐞</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>𝐞</mml:mi> <mml:mo>−</mml:mo> </mml:msup> </mml:mstyle> </mml:math> annihilation at low energies provides important information about interactions of light quarks and spectroscopy of their bound states. These studies are especially important for theoretical calculations of the muon \bm{(g-2)} <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mstyle mathvariant="bold"> <mml:mo stretchy="false" form="prefix">(</mml:mo> <mml:mi>𝐠</mml:mi> <mml:mo>−</mml:mo> <mml:mn>2</mml:mn> <mml:mo stretchy="false" form="postfix">)</mml:mo> </mml:mstyle> </mml:math> via the Standard Model because of the present difference between theoretical and experimental values exceeds three standard deviations. In this report we will discuss current status and recent results obtained by the CMD-3 experiment and will give a brief look to status of the BaBar and Belle II experiments.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.105 | 0.013 |
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".