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Constraints on exclusive branching fractions $${\mathcal {B}}_i(B^+\rightarrow X_c^il^+\nu )$$ B i ( B + → X c i l + ν ) from moment measurements in inclusive $$B\rightarrow X_cl\nu $$ B → X c l ν decays

2014· article· en· W20354690 on OpenAlexaff
F. U. Bernlochner, D. Biedermann, Heiko Lacker, Thomas Lück

Bibliographic record

VenueThe European Physical Journal C · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPhysicsBranching fractionHadronParticle physicsBranching (polymer chemistry)CrystallographyCombinatoricsChemistryMathematics

Abstract

fetched live from OpenAlex

As an alternative to direct measurements, we extract the branching fractions $${\mathcal {B}}_i(B^+\rightarrow X_c^il^+\nu )$$ 1 with $$X_c^i=D,D^*,D_0,D'_1,D_1,D_2,D',D'^{*}$$ and non-resonant final states $$(D^{(*)}\pi )_{nr}$$ , from a fit to electron energy, hadronic mass and combined hadronic mass–energy moments measured in inclusive $$B\rightarrow X_cl\nu $$ decays. The fit is performed by constraining the sum of exclusive branching fractions to the measured $${\mathcal {B}} (B^+\rightarrow X_c l^+\nu )$$ value, and with different sets of additional constraints for the directly measured branching fractions. There is no fit scenario in which a single branching fraction can close the gap between $${\mathcal {B}} (B^+\rightarrow X_c l^+\nu )$$ and the sum of known branching fractions $${\mathcal {B}}_i(B^+\rightarrow X_c^il^+\nu )$$ . The fitted $${\mathcal {B}}(B^+\rightarrow \overline{D}^{*0}l^+\nu )$$ is found to be significantly larger than its direct measurement. $${\mathcal {B}}(B^+\rightarrow \overline{D}^0l^+\nu )$$ is in good agreement with the direct measurement; when $${\mathcal {B}}(B^+\rightarrow \overline{D}^{*0} l^+\nu )$$ is constrained the fitted $${\mathcal {B}}(B^+\rightarrow \overline{D}^0l^+\nu )$$ increases. Within large uncertainties, $${\mathcal {B}}(B^+\rightarrow \overline{D}'^0_1l^+\nu )$$ agrees with direct measurements. Depending on the fit scenario, $${\mathcal {B}}(B^+\rightarrow \overline{D}^0_0l^+\nu )$$ is consistent with or larger than its direct measurement. The fit is not able to easily disentangle $$B^+\rightarrow \overline{D}^0_1l^+\nu $$ and $$B^+\rightarrow \overline{D}^0_2l^+\nu $$ , and tends to increase the sum of these two branching fractions. $${\mathcal {B}} (B^+\rightarrow (D^{(*)}\pi )_{nr}l^+\nu )$$ with non-resonant $$(D^{(*)}\pi )_{nr}$$ final states is found to be of the order $$0.3~\%$$ . No indication is found for significant contributions from so far unmeasured $$B^+\rightarrow \overline{D}'^{(*)0}l^+\nu $$ decays.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.021
GPT teacher head0.279
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations6
Published2014
Admission routes1
Has abstractyes

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