For each word, we run 1-through 6-preceding-word windows through the classifier, and 1-through 6-word windows beginning with the word, for a total of 12 windows, yielding for each window a result like: For each of the 12 results, we extract three features: the identity of the top-scoring language, here, Swedish; the confidence score in the top-scoring language, here, 0.235; and the score difference between the target language (English for these experiments) and the top-scoring non-target language, here, 0.148 − 0.235 = −0.087.
the classifier for "mixed"-quality data and the "gazetteer" model were each trained on that set plus the "Latin" training set and the supplemental set.