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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 10, 695-708, 2017
http://www.atmos-meas-tech.net/10/695/2017/
doi:10.5194/amt-10-695-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
03 Mar 2017
Evaluation of machine learning algorithms for classification of primary biological aerosol using a new UV-LIF spectrometer
Simon Ruske et al.
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'Manuscript Review - Reviewer 1', Darrel Baumgardner, 01 Sep 2016 Printer-friendly Version 
AC1: 'Response to Referee #1', S. Ruske, 25 Oct 2016 Printer-friendly Version Supplement 
 
RC2: 'Review of Ruske et al.', Anonymous Referee #2, 07 Sep 2016 Printer-friendly Version 
AC2: 'Response to referee #2', S. Ruske, 25 Oct 2016 Printer-friendly Version Supplement 
Publications Copernicus
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Short summary
Particles such as bacteria, pollen and fungal spores have important implications within the environment and public health sectors. Here we evaluate the performance of various different methods for distinguishing between these different types of particles using a new instrument. We demonstrate that there may be better alternatives to the currently used methods which can be further investigated in future research.
Particles such as bacteria, pollen and fungal spores have important implications within the...
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