[asdff]

In some fields the scientific software is actually simple, no crazy math. But rather than esoteric math knowledge there are say baked in assumptions and context from the domain that is hard to gleam from the outside without steeping yourself in the field to the point you might as well earn a PhD from it. And of course the same issues where there is no funding for long term support. Not necessarily as big an issue as with general software on that though, because the tools are generally complete in the “does what it says on the tin” sense, no new features are planned nor needed per say, no security considerations, it is probably written in a decades old language that will be around for decades still, etc.