In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

Q: The results indicate that most performance gains come from words embeddings, style, and morality features. Other features (emotion and sentiment) show lower importance: nevertheless, they still improve the overall system performance (on average 0.35% Macro-F$_1$ improvement) 
 Question: Based on this paper, what is the more predictive set of features to detect fake news?

A: words embeddings, style, and morality features
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Q: The corpus is freely available at the following link 
 Question: Is this dataset publicly available?

A: Yes
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Q:  Our final survey based classification results showed an accuracy of 96% in detecting PTSD and mean squared error of 1.2 in estimating its intensity given we have four intensity, No PTSD, Low Risk PTSD, Moderate Risk PTSD and High Risk PTSD with a score of 0, 1, 2 and 3 respectively.  
 Question: How is the intensity of the PTSD established?

A:
Given we have four intensity, No PTSD, Low Risk PTSD, Moderate Risk PTSD and High Risk PTSD with a score of 0, 1, 2 and 3 respectively, the estimated intensity  is established as mean  squared error.
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