It's not reasonable, but for different reasons. Building a carbon copy of LHC would not add anything new in the way of science. A better example would be LIGO. Adding another gravity wave detector of the exact same spec but halfway around the world would be fantastic, because it increases our triangulation ability, and keeping the engineering, hardware, and software the same reduces cognitive load of the scientists running it. Yes that means any "bug" in the first is present in the second, but that also means you have a common baseline. In fact there will inevitably be discrepancies in implementation (no two engineering projects are identical, even with the same blueprint), and you can leverage that high degree of similarity to reduce the search space (so long as subsystems are sufficiently modular, and the software is a direct copy).
The original comment was with respect to some n-back training program. There's so many other potential places of bias in an experiment like that, that you'd be foolish not to start with the exact same program. If an independent team uses a different software stack, and can't replicate, was it the different procedure, software, subjects, or noise?
The first step in scientific replication is almost always, "can the experiment be replicated, or was it a fluke?" In this stage, you want to minimize any free variables.
It's a matter of (leaky) abstractions. If I'm running a chemistry replication, I don't need the exact same round bottom flask as the original experiment; RBFs are fungible. In fact I could probably scale to a different size RBF. However, depending on the chemistry involved, I probably don't want to run the reaction in a cylindrical reactor, at least not without running in the RBF first. That has a different heating profile, which could generate different impurities.
Likewise, I probably don't need the exact same make/model of chromatograph. However, I do want to use the same procedure for running the chromatograph.
The original comment was with respect to some n-back training program. There's so many other potential places of bias in an experiment like that, that you'd be foolish not to start with the exact same program. If an independent team uses a different software stack, and can't replicate, was it the different procedure, software, subjects, or noise?
The first step in scientific replication is almost always, "can the experiment be replicated, or was it a fluke?" In this stage, you want to minimize any free variables.
It's a matter of (leaky) abstractions. If I'm running a chemistry replication, I don't need the exact same round bottom flask as the original experiment; RBFs are fungible. In fact I could probably scale to a different size RBF. However, depending on the chemistry involved, I probably don't want to run the reaction in a cylindrical reactor, at least not without running in the RBF first. That has a different heating profile, which could generate different impurities.
Likewise, I probably don't need the exact same make/model of chromatograph. However, I do want to use the same procedure for running the chromatograph.