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In non-generally relativistic theories the spacetime metric is frozen to a single value assignment for all times and all solutions: it is model independent.
Because the edge location has only a small bias, the error of our algorithm is noise limited, and in the absence of noise, it is model limited.
The main advantage of our method is that it is model independent, i.e., it can be applied with any classifier that provides a probability estimate for a prediction.
Again, it is Model 1 that was viewed most negatively, with Model 4 receiving some support; interestingly Model 1 had the biggest increase in acceptability after the discussion and information session.
With this data-driven approach, our proposed approach is versatile: it is compatible with other data sources, and it is model agnostic and thus compatible with user equilibrium, system-optimum, Stackelberg concepts, and other models.
In that capacity, it is model of crap contrarianism.
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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