One approach to predicting the folded structure of a polymer (DNA, RNA, protein) is to compute the probability that any particular part of the polymer $x_i$ is "paired" with another part of the polymer $x_j$, per molecule of polymer in a solution at equilibrium. This pairing probability is often computed by enumerating all conformations where $x_i$ is paired with $x_j$, summing over the free energy of all such conformations, and then evaluating a Boltzmann distribution.
More precisely, to compute the probability that a polymer adopts a particular conformation $s$, per molecule of polymer in solution at equilibrium, one computes:
$$P(s) = \exp(-G_s/RT)/Z$$
where $G_s$ is the free energy of conformation $s$ and $Z$ is the partition function a.k.a normalization factor needed so that $P$ is a probability distribution.
The question: Is this a rigorous way to compute $P(s)$?
The reason I doubt the rigorousness of the above computation is that I can get widely different results for $P(s)$ by making very slightly different assumptions about the polymer in question.
Why I believe $P(s)$ is ill-defined:
First, let's take a very simple polymer with just two components and two states: UNPAIRED and PAIRED. Say that the chemical potential of UNPAIRED is $-1$ kcal mol$^{-1}$ and the chemical potential of PAIRED is $-1$ kcal mol$^{-1}$. Then $P($UNPAIRED$)$ is $1/2$, which seems very reasonable.
But, let's say that we add a little bit more complexity to our model for the polymer and split PAIRED into 5 states, which are each very slightly different versions of PAIRED (but they are, in fact, different). These new states, PAIRED$_{i}$ for $i = 1, 2, ... 5$ still have chemical potential $-1$ kcal mol$^{-1}$, and UNPAIRED still has chemical potential $-1$. Now, $P($UNPAIRED$)$ is $1/6$.
Both models accurately describe the polymer, however the latter is slightly more precise. However, it seems that $P(s)$ is sensitive to such changes in the model. To what extent, then, is $P(s)$ rigorous?