An insightful study that's replicable (but has not yet been) is valuable. A lousy study that's been replicated five times (not because it's interesting, but because it was easy to do, and the replicators knew that they'd be rewarded for replicating anything) is not valuable.
A metric that says "number of studies" is IMHO even more arbitrary, more gameable, and more detached from actual value than citation count - which does have some notion that your study actually matters to other poeple; that it was worth writing that paper because someone read it.
Or, I dunno, paleontology or sociology or other stuff.
Citations can be a useful metric here, particularly if you can identify citations of people actually using the method (as opposed to people just mentioning it in passing, or other methodological researchers comparing their own methods to it).
The number of people who did and gave their approval would be a good indicator I can trust the paper.
What does a citation do that's better then this?
For experiments, or non math papers, you might need something more robust. I think mostly because reviewing the paper isn't really reviewing the full study, but only what the researcher put in the paper. So it is very hard to review methodology and details to be sure they followed proper protocols, etc. You'd need someone to have been reviewing the study as it is happening, and not just the output paper from it.
Consider Researcher A, who has one paper with a hundred citations, and Researcher B, who has ten papers with two citations each. Probably Researcher A has made a larger contribution.
Whether you're in math or any other field, the fact that a paper is correct or reasonable enough to make it past peer review doesn't mean anybody gives a shit about it.
Would both help solve the replication crisis, and resolve this problem.
Of course then you might have 10 000 studies replicating the same easy to do study... which is why the "score" should be reduced based on how many other times that study has been replicated.