2021
DOI: 10.1103/physrevd.104.012008
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Measurements of partial branching fractions of inclusive BXu+ν decays with hadronic tagging

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Cited by 25 publications
(44 citation statements)
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“…A possible approach to evading this criticism was presented recently in the reanalysis of the Belle data in ref. [7], where kinematic properties were not included as input features in a BDT classifier. Although the classification power of such a BDT is reduced when viewed in terms of typical machine-learning metrics such as the area under the curve, it can be used to enhance the signal-to-background ratio to a level which permits a binned one-and two-dimensional likelihood analyses of the kinematic features of the signal and background after event selection resulting in a similar significance after the likelihood analysis.…”
Section: Jhep01(2022)143mentioning
confidence: 99%
See 2 more Smart Citations
“…A possible approach to evading this criticism was presented recently in the reanalysis of the Belle data in ref. [7], where kinematic properties were not included as input features in a BDT classifier. Although the classification power of such a BDT is reduced when viewed in terms of typical machine-learning metrics such as the area under the curve, it can be used to enhance the signal-to-background ratio to a level which permits a binned one-and two-dimensional likelihood analyses of the kinematic features of the signal and background after event selection resulting in a similar significance after the likelihood analysis.…”
Section: Jhep01(2022)143mentioning
confidence: 99%
“…We have chosen this set of high-level features to mimic the feature selection in the BDT analyses performed by Belle in refs. [5,7]. Some differences with respect to the sets used in those papers arise, because we do not have access to all experimental features in our simplified detector simulation, for instance features related to the quality of the signal reconstruction.…”
Section: Input Featuresmentioning
confidence: 99%
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“…This DFN model contains α s corrections convoluted with the non-perturbative shape function in an ad-hoc exponential model [29]. The two parameters of this shape function in the Kagan-Neubert scheme are taken from a fit to B → X c ν and B → X s γ data [30] (see also [31]). In the figures, the points labelled DFN present the central values of the DFN, while…”
Section: Comparison Between Theory and Monte-carlomentioning
confidence: 99%
“…These variations can be used to estimate the error of the DFN model. This method, using the variation of the DFN models as an error, is used at Belle (see also the recent Belle analysis of theB → X u ν [31]). For both the DFN and the BLNP models, resonant contributions are included using a "hybrid Monte Carlo".…”
Section: Comparison Between Theory and Monte-carlomentioning
confidence: 99%