Briefly, no. Why: they're most likely not training your average ML models on this dataset. Instead, they are likely taking a model of some physics and seeing how it performs in these simulations.
You can think of this as a form of causal inference - "if this model is true, how well does it work with our current understanding (simulations) of physics?" type of questions. There are measures of error and bias that come with evaluation of these models.
You can think of this as a form of causal inference - "if this model is true, how well does it work with our current understanding (simulations) of physics?" type of questions. There are measures of error and bias that come with evaluation of these models.