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Crime Science

, 7:20 | Cite as

Correction to: Towards a ‘smart’ cost–benefit tool: using machine learning to predict the costs of criminal justice policy interventions

  • Matthew Manning
  • Gabriel T. W. Wong
  • Timothy Graham
  • Thilina Ranbaduge
  • Peter Christen
  • Kerry Taylor
  • Richard Wortley
  • Toni Makkai
  • Pierre Skorich
Open Access
Correction

Correction to: Crime Sci (2018) 7:12 https://doi.org/10.1186/s40163-018-0086-4

The original version of the article (Manning et al. 2018) contained an error in the funding section and name of an author. The correction funding note should be

This project was funded by the Economic & Social Research Council grant (ESRC Reference: ES/L007223/1) titled ‘University Consortium for Evidence-Based Crime Reduction’, the Australian National University’s Cross College Grant and the Jill Dando Institute of Security and Crime Science.

The author name was spelt incorrectly as Cristen instead of Christen.

The original article has been corrected.

Notes

Publisher's Note

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Reference

  1. Manning, M., Wong, G. T. W., Graham, T., Ranbaduge, T., Christen, P., Taylor, K. (2018). Towards a ‘smart’ cost–benefit tool: using machine learning to predict the costs of criminal justice policy interventions. Crime Sci, 7, 12.  https://doi.org/10.1186/s40163-018-0086-4.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.ANU Centre for Social Research and MethodsAustralian National UniversityCanberraAustralia
  2. 2.Research School of Computer ScienceAustralian National UniversityCanberraAustralia
  3. 3.Jill Dando Institute of Security and Crime ScienceUniversity College LondonLondonUK
  4. 4.Australian Public ServiceCanberraAustralia

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