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In practice, this means that only the model elements of the profile are visible for the modeler while other UML-related elements are hidden from the tool.
It is suspected that ontology-based support could require additional effort for the modeler.
The complex constitutive behaviors, large displacements, and prevalence of discontinuities in geologic systems, pose unique challenges for the modeler.
Second, they normally assume that the data we see come from a regular process of random shocks, with strong incentives for the modeler to assume that the shocks are more or less normal, not involving large, low probability events – which leaves you unready for the Big One when it happens.
One possible question for the modeler could be: how independent from each other the information provided by each descriptor is?
Normally, this specification menu has UML-related properties of model element but due to customization of the tool, only domain-related concepts are visible for the modeler.
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For example, the modeler can decide how a delete action propagates through model structure, or which default values to use for newly created species.
For example, the modeler might start by developing a suitable pharmacokinetic (PK) model, followed by a PD model for placebo subjects and finally a full PKPD model for all data, active and placebo.
The data within the Summary Database (SDB) function provides justifications for choices made by the modeler when designing the model.
If unweighted averaging is conducted, the average outcome will simply reflect the distribution of models chosen by the modeler for inclusion.
For example, if the modeler defines a reaction like "-> A", then s/he is implicitly saying that a species A should exist in the model.
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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