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Highly accurate classification of biological spores by culture medium for forensic attribution using multiple chemical signature types and machine learning

Crossref DOI link: https://doi.org/10.1007/s00216-020-02660-2

Published Online: 2020-04-23

Published Print: 2020-07

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Ippoliti, Paul

Nargi, Fran

Han, Jason

Casale, Amanda

Walsh, Matthew

Boettcher, Tara

Dettman, Josh
License Information

Text and Data Mining valid from 2020-04-23

Version of Record valid from 2020-04-23
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Article History

Received: 24 January 2020

Revised: 1 April 2020

Accepted: 14 April 2020

First Online: 23 April 2020

Compliance with ethical standards

:

: The authors declare that they have no conflict of interest.

: Approved for public release. Distribution is unlimited. This material is based upon work supported under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the US Air Force.

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