Detailed Instructions: In this task, you are given a abstract of article and corresponding title of an article. Your task is to generate label "yes" if title is right for article, otherwise generate "no".
Q: Abstract: This paper presents a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic. This estimator does not depend on a formal model of the structure of the heteroskedasticity. By comparing the elements of the new estimator to those of the usual covariance estimator, one obtains a direct test for heteroskedasticity, since in the absence of heteroskedasticity, the two estimators will be approximately equal, but will generally diverge otherwise. The test has an appealing least squares interpretation.. Title: Isolation of a Fusion Transcript, AMLl IETO, With Similarity to
A:
no