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This was true for all models considered with or without Stern layer.
This is true for all models and parameterisation methods.
However, an evolutionary model involving a local clock for this branch (with all other branches evolving at the same rate) still fits the data significantly worse than the model without a clock (P < 10-12, Table 2); the same is indeed true for all models involving a single local clock (data not shown).
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We found these predictions to be true for all model parameter values, α 1, α 2, β 1 > 0, m > 1.
This was true for all subsequent models.
However, it can be seen that this is not true for all null-models.
Note that stabilization at a positive rate requires that ν0 > 0 and C > 0. The first condition states that, in the absence of any input, the neuron does not show any spontaneous activity, and this is trivially true for all standard neuron models, including the integrate-and-fire model.
This is true for all spike-generation models considered.
This universal/existential dichotomy is a familiar one to logicians in formal logics there exists a proof for a formula \(X\) if and only if \(X\) is true in all models for the logic.
This was true for all 14 MODELTEST substitution models (Table 2) except for the simplest, JC model.
This statement is possibly (probably) true for all general outcome prediction models.
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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