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Bibliographic record
Abstract
Using the entire sample of $467\ifmmode\times\else\texttimes\fi{}{10}^{6}$ $\ensuremath{\Upsilon}(4S)\ensuremath{\rightarrow}B\overline{B}$ decays collected with the BABAR detector at the PEP-II asymmetric-energy $B$ factory at the SLAC National Accelerator Laboratory, we perform an analysis of ${B}^{\ifmmode\pm\else\textpm\fi{}}\ensuremath{\rightarrow}D{K}^{\ifmmode\pm\else\textpm\fi{}}$ decays, using decay modes in which the neutral $D$ meson decays to either $CP$-eigenstates or non-$CP$-eigenstates. We measure the partial decay rate charge asymmetries for $CP$-even and $CP$-odd $D$ final states to be ${A}_{CP+}=0.25\ifmmode\pm\else\textpm\fi{}0.06\ifmmode\pm\else\textpm\fi{}0.02$ and ${A}_{CP\ensuremath{-}}=\ensuremath{-}0.09\ifmmode\pm\else\textpm\fi{}0.07\ifmmode\pm\else\textpm\fi{}0.02$, respectively, where the first error is the statistical and the second is the systematic uncertainty. The parameter ${A}_{CP+}$ is different from zero with a significance of 3.6 standard deviations, constituting evidence for direct $CP$ violation. We also measure the ratios of the charged-averaged $B$ partial decay rates in $CP$ and non-$CP$ decays, ${R}_{CP+}=1.18\ifmmode\pm\else\textpm\fi{}0.09\ifmmode\pm\else\textpm\fi{}0.05$ and ${R}_{CP\ensuremath{-}}=1.07\ifmmode\pm\else\textpm\fi{}0.08\ifmmode\pm\else\textpm\fi{}0.04$. We infer frequentist confidence intervals for the angle $\ensuremath{\gamma}$ of the unitarity triangle, for the strong phase difference ${\ensuremath{\delta}}_{B}$, and for the amplitude ratio ${r}_{B}$, which are related to the ${B}^{\ensuremath{-}}\ensuremath{\rightarrow}D{K}^{\ensuremath{-}}$ decay amplitude by ${r}_{B}{e}^{i({\ensuremath{\delta}}_{B}\ensuremath{-}\ensuremath{\gamma})}=A({B}^{\ensuremath{-}}\ensuremath{\rightarrow}{\overline{D}}^{0}{K}^{\ensuremath{-}})/A({B}^{\ensuremath{-}}\ensuremath{\rightarrow}{D}^{0}{K}^{\ensuremath{-}})$. Including statistical and systematic uncertainties, we obtain $0.24<{r}_{B}<0.45$ ($0.06<{r}_{B}<0.51$) and, modulo 180\ifmmode^\circ\else\textdegree\fi{}, $11.3\ifmmode^\circ\else\textdegree\fi{}<\ensuremath{\gamma}<22.7\ifmmode^\circ\else\textdegree\fi{}$ or $80.8\ifmmode^\circ\else\textdegree\fi{}<\ensuremath{\gamma}<99.2\ifmmode^\circ\else\textdegree\fi{}$ or $157.3\ifmmode^\circ\else\textdegree\fi{}<\ensuremath{\gamma}<168.7\ifmmode^\circ\else\textdegree\fi{}$ ($7.0\ifmmode^\circ\else\textdegree\fi{}<\ensuremath{\gamma}<173.0\ifmmode^\circ\else\textdegree\fi{}$) at the 68% (95%) confidence level.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.015 |
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".