Assume you have data for Hooke's law (a spreadsheet with F, x, and other variables) and you want AlphaEvolve to give you the equation ``F = -C_1*x``.

Let's say the model hallucinates in two directions:

1. "There is a trigonometric relationship between variable F and x". It expresses this as ``F = -C_1*sin(x)``. You fit the constant C_1 w.r.t the dataset, execute the program, and your best fit has a high error. You can discard the program.

2. "There is an inverse linear relationship between variable F and x". Now it expresses this as ``F = -C_1*x``. You fit the constant C_1 w.r.t the dataset, execute the program, and your best fit has extremely low error. You now know for sure that you're on the right track.