You'll note that the paper you cite observes that g consistently predicts performance well, and that assessing "more than g" consistently fails to improve the quality of predictions.

And then it goes on to conclude that "If the goal is to do a good job in prediction... it makes sense to use the most general measures available" and "If predictive efficiency is the goal, it will be hard to consistently beat g."

It's an opinion piece arguing that, because the concept of g provides no mechanistic insight into how people solve problems, studies that seek to explain how problems get solved (as opposed to whether problems will get solved) should try to explain that process in terms of factors at the second-highest level of abstraction, rather than the highest level.