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Centrality measures, or at least popular interpretations of these measures, make implicit assumptions about the manner in which traffic flows through a network.
State-of-the-art approaches, however, tend to make implicit assumptions about the language used in labels (usually English) and are either domain-agnostic or are built for a specific domain.
In these cases, it is common to make implicit assumptions that the underlying opinions or beliefs of subjects – the ones that are mapped into the Likert item data – are Gaussian distributed.
Centrality indices make implicit assumptions about the manner in which traffic flows through a network and are used to produce a ranking of the nodes according to their importance.
In this work we were hence able to show that (1) targets (here kinases) with few shared activities are difficult to establish neighborhood relationships for, and (2) phylogenetic tree representations make implicit assumptions (i.e. that neighboring kinases exhibit similar interaction profiles with inhibitors) that are not always suitable for analyses of bioactivity space.
These methods are most well developed for single nucleotide polymorphism (SNP) changes in typing data (as opposed to whole genome sequences) and make implicit assumptions about the human genomic structure, diploidy, and recombination rates [ 12- 14].
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Each normalization strategy makes implicit assumptions about the biology that impacts our interpretation of the data.
Making implicit assumptions visible to different stakeholders can enable the use of this understanding to craft solutions acceptable to the involved parties.
The goal, in particular, is to identify which assumptions are really crucial — and in so doing to catch yourself when you're making implicit assumptions that can't stand clear scrutiny.
Either way, an important point is that any version of the dream argument that appeals to real-world dreams, for instance by making implicit assumptions about what it is actually or even typically like to dream, is open to empirical investigation.
As the expert developing an NRDR knowledge base invents new concepts, s/he makes implicit assumptions about any concepts that s/he introduces, in that s/he has a certain disposition about what these concepts mean and when they do actually apply.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com