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Bibliographic record
Abstract
We present searches for the rare decay modes ${D}^{0}\ensuremath{\rightarrow}{e}^{+}{e}^{\ensuremath{-}}$, ${D}^{0}\ensuremath{\rightarrow}{\ensuremath{\mu}}^{+}{\ensuremath{\mu}}^{\ensuremath{-}}$, and ${D}^{0}\ensuremath{\rightarrow}{e}^{\ifmmode\pm\else\textpm\fi{}}{\ensuremath{\mu}}^{\ensuremath{\mp}}$ in continuum ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}c\overline{c}$ events recorded by the BABAR detector in a data sample that corresponds to an integrated luminosity of $468\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$. These decays are highly Glashow--Iliopoulos--Maiani suppressed but may be enhanced in several extensions of the standard model. Our observed event yields are consistent with the expected backgrounds. An excess is seen in the ${D}^{0}\ensuremath{\rightarrow}{\ensuremath{\mu}}^{+}{\ensuremath{\mu}}^{\ensuremath{-}}$ channel, although the observed yield is consistent with an upward background fluctuation at the 5% level. Using the Feldman--Cousins method, we set the following 90% confidence level intervals on the branching fractions: $\mathcal{B}({D}^{0}\ensuremath{\rightarrow}{e}^{+}{e}^{\ensuremath{-}})<1.7\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}7}$, $\mathcal{B}({D}^{0}\ensuremath{\rightarrow}{\ensuremath{\mu}}^{+}{\ensuremath{\mu}}^{\ensuremath{-}})$ within $[0.6,8.1]\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}7}$, and $\mathcal{B}({D}^{0}\ensuremath{\rightarrow}{e}^{\ifmmode\pm\else\textpm\fi{}}{\ensuremath{\mu}}^{\ensuremath{\mp}})<3.3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}7}$.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.192 | 0.118 |
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".