@article{ref1,
title="Beyond prediction: using big data for policy problems",
journal="Science",
year="2017",
author="Athey, Susan",
volume="355",
number="6324",
pages="483-485",
abstract="Machine-learning prediction methods have been extremely productive in applications ranging from medicine to allocating fire and health inspectors in cities. However, there are a number of gaps between making a prediction and making a decision, and underlying assumptions need to be understood in order to optimize data-driven decision-making.<br><br>Copyright © 2017, American Association for the Advancement of Science.<p /> <p>Language: en</p>",
language="en",
issn="0036-8075",
doi="10.1126/science.aal4321",
url="http://dx.doi.org/10.1126/science.aal4321"
}