More cases and/or possibilities can be added to the algorithm in the future, but the results given by Figure 3 (bottom panel), show the method’s performance is at the level of $\approx 90$ %. In summary we list the limitations of the method:

1.  From the beginning, if the photoionization components (e.g., wabs1 and/or wabs2) are not globally fitting the spectrum, the ID process will be dubious.

2.  The method expects a list of detected features. If as part of a blend, only one feature is given, the method will ID it as the strongest one, regardless the micro-physics of the blend.

3.  The method will not identify a case where the physics changes the ratio $\lambda(T)_1/\lambda(T)_2 > 1$ to $<1$ (e.g., case b of Figure \[cases1\]).

4.  Naturally, if the continuum is not well established in the building of the physical model, at the beginning of the process, the absolute measurement of EWs will be wrong (though the comparison between them will be good since they all use the same continuum).

5.  The algorithm does not allow the ID of two-velocity component of a feature under the configuration given by case c) of Figure \[cases1\]. In all those cases 