Update docs/src/inverse_problems/structural_identifiability.md

Co-authored-by: Sam Isaacson <[email protected]>

Author: TorkelE

docs/src/inverse_problems/structural_identifiability.md

@@ -100,7 +100,7 @@ find_identifiable_functions(goodwind_oscillator; measured_quantities=[:M], logle
 ```
 Again, these results are consistent with those produced by `assess_identifiability`. There, `pₑ` and `pₚ` where found to be globally identifiable. Here, they correspond directly to identifiable expressions. The remaining four parameters (`pₘ`, `dₘ`, `dₑ`, and `dₚ`) occur as part of more complicated composite expressions.
 
-The `find_identifiable_functions` functions tries to simplify its output functions to create nice expressions. The degree to which it does this can be adjusted using the `simplify` keywords. Using the `:weak`, `:standard` (default), and `:strong` arguments, increased simplification can be forced (at the expense of longer runtimes).
+`find_identifiable_functions` tries to simplify its output functions to create nice expressions. The degree to which it does this can be adjusted using the `simplify` keywords. Using the `:weak`, `:standard` (default), and `:strong` arguments, increased simplification can be forced (at the expense of longer runtime).
 
 ## Creating StructuralIdentifiability compatible ODE models from Catalyst `ReactionSystem`s
 While the functionality described above covers the vast majority of analysis that user might want to perform, the StructuralIdentifiability package supports several additional features. While these does not have inherent Catalyst support, we do provide the `make_si_ode` function to simplify their use. Similar to the previous functions, it takes a `ReactionSystem`, lists of measured quantities, and known parameter values. The output is a [ODE of the standard form supported by StructuralIdentifiability](https://docs.sciml.ai/StructuralIdentifiability/stable/tutorials/creating_ode/#Defining-the-model-using-@ODEmodel-macro). It can be created using the following syntax: