Yes, I think that this is the crux of the matter here, and I agree that merely funding direct, vanilla replication is not the optimal solution here and would not solve many of the problems we're facing. I'm really talking about the idea from the thread I linked in my original comment--the idea of "red teams" for science. There's probably a number of ways to accomplish this, and direct replication could play a role, but I imagine that a funding agency tasked with funding red teams for other government-funded research would lean towards a more diverse and holistic toolkit. You'd certainly need to have some mechanisms for "watching the watchers," but again, very few researchers I've met are stupid, many of them actually care pretty deeply about ethics and scientific integrity, and would probably jump at the chance for a steady paycheck while helping to advance that.
> Science has no formal mechanisms to detect made up or fraudulent data sets, which is a real problem [...]
This isn't strictly true (I'd like encourage people not to use "Science" as a proper noun; I think it's actually a bit unhelpful). I think a common approach to performing research using the scientific method often (almost always?) involves using observation across multiple instances, then using statistics to draw a generalized conclusions based on the group of observations. And statistics does have formal methods for identifying potentially fraudulent datasets, some of which a Dr. Hilgard does a great job of explaining in an actual case of research fraud he found in this article[1].
[1] https://crystalprisonzone.blogspot.com/2021/01/i-tried-to-re...