Study of Inclusive $B^-$ and $\bar{B}^0$ Decays toFlavor-Tagged $D$, $D_s$ and $\Lambda_c$
Bibliographic record
Abstract
We report on a study of inclusive B{sup -} and {bar B}{sup 0} meson decays to D{sup 0}X, {bar D}{sup 0}X, D{sup +}X, D{sup -}X, D{sub s}{sup +}X, D{sub s}{sup -}X, {Lambda}{sub c}{sup +}X, {bar {Lambda}}{sub c}{sup -}X, based on a sample of 231 million B{bar B} events recorded with the BABAR detector at the {Upsilon}(4S) resonance. Events are selected by completely reconstructing one B and searching for a reconstructed charm particle in the rest of the event. From the measured branching fractions of these decays, we infer the number of charm and anti-charm particles per {bar B} decay, separately for charged and neutral parents. We derive the total charm yield per B{sup -} decay, n{sub c}{sup -} = 1.202 {+-} 0.023 {+-} 0.040{sub -0.029}{sup +0.035}, and per {bar B}{sup 0} decay, n = 1.193 {+-} 0.030 {+-} 0.034{sub -0.035}{sup +0.044} where the first uncertainty is statistical, the second is systematic, and the third reflects the charm branching-fraction uncertainties. We also present the charm momentum distributions measured in the {bar 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".