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Bibliographic record
Abstract
We present an observation of $B\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{K}^{*}$. The data sample corresponds to $232\ifmmode\times\else\texttimes\fi{}{10}^{6}$ $B\overline{B}$ pairs collected with the BABAR detector at the PEP-II asymmetric-energy $B$ factory at the Stanford Linear Accelerator Center. We measure the branching fractions (in units of ${10}^{\ensuremath{-}6}$) $\mathcal{B}({B}^{0}\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{K}^{*0})=3.8\ifmmode\pm\else\textpm\fi{}1.1\ifmmode\pm\else\textpm\fi{}0.5$ and $\mathcal{B}({B}^{+}\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{K}^{*+})={4.9}_{\ensuremath{-}1.7}^{+1.9}\ifmmode\pm\else\textpm\fi{}0.8$, where the first error is statistical and the second systematic. A simultaneous fit results in the observation of $B\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{K}^{*}$ with $\mathcal{B}(B\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{K}^{*})={4.1}_{\ensuremath{-}0.9}^{+1.0}\ifmmode\pm\else\textpm\fi{}0.5$. We also search for $B\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}\ensuremath{\rho}$ and ${\ensuremath{\eta}}^{\ensuremath{'}}{f}_{0}(980)({f}_{0}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}})$ with results and 90% confidence level upper limits $\mathcal{B}({B}^{+}\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{\ensuremath{\rho}}^{+})={8.7}_{\ensuremath{-}2.8\ensuremath{-}1.3}^{+3.1+2.3}$ ($<14$), $\mathcal{B}({B}^{0}\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{\ensuremath{\rho}}^{0})<3.7$, and $\mathcal{B}\mathbf{(}{B}^{0}\ensuremath{\rightarrow}{\ensuremath{\eta}}^{\ensuremath{'}}{f}_{0}(980)({f}_{0}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}})\mathbf{)}<1.5$. Charge asymmetries in the channels with significant yields are consistent with zero.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.216 | 0.107 |
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".