In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

[Q]: We recruited 100 crowdworkers on Amazon Mechanical Turk (AMT) and measured completion times and accuracies for typing randomly sampled sentences from the Yelp corpus. 
[A]: What user variations have been tested?


[Q]: Within ICU notes (e.g., text example in top-left box in Figure 2), we first identify all abbreviations using regular expressions and then try to find all possible expansions of these abbreviations from domain-specific knowledge base as candidates.
[A]: Do they use any knowledge base to expand abbreviations?


[Q]:  To evaluate real-world performance of our selected classifier (i.e., performance in the absence of model and parameter bias), we perform classification of the holdout set. On this set, our classifier had an accuracy and F1-score of 89.6% and 89.2%, respectively. 
[A]:
What was their system's performance?