The geometric mean of the frequencies of compound parts and the probability estimated from the language model usually attain a high recall, given they are based on unigram features which are easy to collect, but they have some weaknesses, as mentioned above.
while Mutual Information is a much more precise metric, it is less likely to have evidence about every single possible pair of compound parts from a corpus, so it suffers from low recall.