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DST has attracted much attention in many fields owing to its counteracting uncertainty merit, such as artificial intelligence research [11, 12], data fusion [13, 14], and has been shown to achieve a satisfactory performance.
Given the rather long data series of 88 years, it is concluded that bivariate flood frequency analysis is expected to carry significant uncertainty and that the quantification and reduction of uncertainty merit greater attention.
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There seems to be sufficient uncertainty to merit attention.
Where patients are involved in clinical decisions, honestly declaring uncertainty has merit.
However, these studies sparked intense debate as they clearly violated the condition of equipoise: that placebo groups are only deemed ethical if there exists sufficient uncertainty regarding the merit of the intervention.
A focus on positive coping strategies to support and maintain well-being in response to stress and uncertainty therefore has theoretical merit.
Among pure-blooded logicians, however, there is still uncertainty as to the merits of fuzziness.
ABPR has the merits of uncertainty reduction on examination records and accurate pairwise preference learning on implicit feedbacks.
DST as a generalization of the Bayesian theory has unique merits in uncertainty processing, based on which a novel combining scheme called DSC is proposed in [10].
RCTs should produce results that resolve or diminish uncertainty concerning the relative merits of comparator interventions.
Further research with explicit focus on existential uncertainty and certainty is merited.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com