Determination of the CKM angle $\phi_{3}$ from a combination of Belle and Belle II results
Bibliographic record
Abstract
We report a determination of the CKM angle $\phi_{3}$, also known as $\gamma$, from a combination of measurements using samples of up to 711~fb$^{-1}$ from the Belle experiment and up to 362~fb$^{-1}$ from the Belle II experiment. We combine results from analyses of $B^+\to DK^+, B^+\to D\pi^+$, and $B^+ \to D^{*}K^+$ decays, where $D$ is an admixture of $D^0$ and $\overline{D}{}^{0}$ mesons, in a likelihood fit to obtain $\phi_{3} = (78.6^{+7.2}_{-7.3})^{\circ}$. We also briefly discuss the interpretation of this result.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".