Do you see the measure of predictive error complexity as having any use in determining when or where intelligence can be objectively identified? "Intelligence" seems to be an abstract entity, and as such it could easily be construed as beyond quantification, not to mention scientific accessibility. My thinking is obviously at a layman's level, but I tend to consider intelligence, information, organization, and design to be inseparable. I also consider them to be accessible to science, if not the stuff of which science is made.
Intelligence is a computational property of a system that can be measured (both directly and indirectly), not something that exists independent of it. There is no more implied intelligence in or behind any "thing" than that which is intrinsic to that thing itself. Predictive error complexity does (with caveats) allow the measure of intelligence (among other things) of systems whose state we cannot fully observe. I do not want to get into the details of it because it is way too technical, but all I can say is that it does not get you where you want to go -- quite the opposite.
Which is what I've been restating over and over. Given some pattern in nature, one cannot assert any more intelligence than that allowed given the algorithmic information content of that pattern. Given some quantity of algorithmic information content, we can assert an upper bound on intelligence. You are trying to invent additional algorithmic information that is entirely unnecessary to generate the observed pattern.