Measurement of Hadronic Mass Moments $\langle M_X^n \rangle $ in $B \rightarrow X_c \ell \nu_\ell\ $ Decays at Belle II
Bibliographic record
Abstract
We present measurements of the first six hadronic mass moments in semileptonic $B \rightarrow X_c \ell \nu_\ell\ $ decays. The hadronic mass moments, together with other observables of inclusive $B$ decays, can be used to determine the CKM matrix element $|{V_{cb}}|$ and mass of the $b$-quark $m_b$ in the context of Heavy Quark Expansions of QCD. The Belle~II data recorded at the $\Upsilon (4S)$ resonance in 2019 and 2020 (March-July), corresponding to an integrated luminosity of $34.6\;\mathrm{fb}^{-1}$, is used for this measurement. The decay $\Upsilon (4S) \rightarrow B \overline{B}$ is reconstructed by applying the hadronic tagging algorithm provided by the Full Event Interpretation to fully reconstruct one $B$ meson. The second $B$ meson is reconstructed inclusively by selecting a high-momentum lepton. The $X_c$ system is identified by the remaining reconstructed tracks and clusters in the electromagnetic calorimeter. We report preliminary results for the hadronic mass moments $\langle M_X^n \rangle $ with $n=1,\dots,6$, measured as a function of a lower cut on the lepton momentum in the signal $B$ rest frame.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".