Training an LinearSVC SVM with 200k samples (half synth and half original) yields a very capable classifiers on the test set.
The best features from the coefs p.o.v. are related to the length of the sentences / documents.
Removing the most important features
Iteratively removing the ten best feature and re-training the model yields very successful models even with very few features.
In particular:
