New limit on the $${\upmu ^+ \rightarrow e^+ \upgamma }$$ decay with the MEG II experiment
Bibliographic record
Abstract
Abstract This letter reports the result of the search for the decay $${\upmu ^+ \rightarrow e^+ \upgamma }$$ μ + → e + γ undertaken at the Paul Scherrer Institut in Switzerland with the MEG II experiment using the data collected in the 2021–2022 physics runs. The sensitivity of the branching ratio measurement in this search is $${2.2 \times 10^{-13}}$$ 2.2 × 10 - 13 , a factor of 2.4 better than that of the full MEG dataset and obtained in a data taking period of about one fourth that of MEG, thanks to the superior performances of the new detector. The observed data are consistent with the expected background, yielding an upper limit on the branching ratio of $$\mathcal{B} ({\upmu ^+ \rightarrow \textrm{e}^+ \upgamma }) < {1.5 \times 10^{-13}}$$ B ( μ + → e + γ ) < 1.5 × 10 - 13 (90% C.L.). Additional improvements are expected with the data collected during the years 2023–2024. The data-taking will continue in the coming years.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".