Alexander Mattick argues that peak accuracy is less important than maintaining a minimum probability of correctness in every state.

“And arguably I would say that the the the the peak accuracy matters very little. Like the the what you need is you need some form of like uh”

“Uh like in every state there is a minimal probability of being correct. Because then you can start doing things like effectively uh like effectively you can throw a common filter against this and do like multiple measurements and actually get the right results. If you have fif percent accuracy and do f whatever many measurements, you co you drop your accuracy uh like you you drop your probability of error very quickly. And I think that right now all of these methods are not set up like this. I think they are set up”