Machine learning approaches for automatic classification of single-particle mass spectrometry data

Wang, Guanzhong; Ruser, Heinrich; Schade, Julian; Passig, Johannes; Adam, Thomas; Dollinger, Günther; Zimmermann, Ralf

doi:https://doi.org/10.5194/amt-17-299-2024

Articles | Volume 17, issue 1

https://doi.org/10.5194/amt-17-299-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-17-299-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 1

Research article

|

16 Jan 2024

Research article |

| 16 Jan 2024

Machine learning approaches for automatic classification of single-particle mass spectrometry data

Guanzhong Wang, Heinrich Ruser, Julian Schade, Johannes Passig, Thomas Adam, Günther Dollinger, and Ralf Zimmermann

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Final revised paper (published on 16 Jan 2024)
Preprint (discussion started on 09 May 2023)

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2023-784', Anonymous Referee #1, 18 Jul 2023

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-784/egusphere-2023-784-RC1-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2023-784-RC1
- AC1: 'Reply on RC1', Guanzhong Wang, 21 Aug 2023
  
  Dear Reviewer,
  We would like to express our gratitude for taking the time to review our manuscript. Your valuable insights and comments have been very helpful in enhancing the quality of our work, and we appreciate your thoughtful evaluation. We understand that timely communication is desired in the review process, and we apologize for our delayed answers .
  We have carefully considered each of your suggestions and concerns, and we are pleased to provide a point-by-point response to address them, please see the supplement.
  Once again, we extend our thanks for your time, effort, and expertise in reviewing our manuscript. We believe that your feedback has been pivotal in shaping the final version of our work.
  Best regards
  Guanzhong Wang
  
  Citation: https://doi.org/10.5194/egusphere-2023-784-AC1
RC2:
'Comment on egusphere-2023-784', Anonymous Referee #2, 12 Sep 2023

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-784/egusphere-2023-784-RC2-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2023-784-RC2
- AC2: 'Reply on RC2', Guanzhong Wang, 09 Oct 2023
  
  Dear Reviewer,
  we would like to express our gratitude for taking the time to review our manuscript. Your valuable insights and comments have been very helpful in enhancing the quality of our work, and we appreciate your thoughtful evaluation. We understand that timely communication is desired in the review process, and we apologize for our delayed answers.
  We have carefully considered each of your suggestions and concerns, and we are pleased to provide a point-by-point response to address them, please see the supplement.
  Once again, we extend our thanks for your time, effort, and expertise in reviewing our manuscript. We believe that your feedback has been pivotal in shaping the final version of our work.
  Best regards, on behalf of the authors
  Guanzhong Wang
  
  Citation: https://doi.org/10.5194/egusphere-2023-784-AC2
- AC3: 'Reply on RC2', Guanzhong Wang, 12 Oct 2023
  
  Dear Reviewer,
  We have uploaded a pdf file of our reply, but now we find that we are unable to download or view the file on the web page. It shows 404 error.
  We contacted the editorial support team and they asked us to re-upload our reply again.
  Thank you in advance.
  Best regards
  Guanzhong Wang
  
  Citation: https://doi.org/10.5194/egusphere-2023-784-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Guanzhong Wang on behalf of the Authors (13 Oct 2023) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (18 Oct 2023) by Hendrik Fuchs

RR by Anonymous Referee #2 (30 Oct 2023)

RR by Anonymous Referee #1 (02 Nov 2023)

ED: Publish as is (02 Nov 2023) by Hendrik Fuchs

AR by Guanzhong Wang on behalf of the Authors (06 Nov 2023) Manuscript

Short summary

This research aims to develop a novel warning system for the real-time monitoring of pollutants in the atmosphere. The system is capable of sampling and investigating airborne aerosol particles on-site, utilizing artificial intelligence to learn their chemical signatures and to classify them in real time. We applied single-particle mass spectrometry for analyzing the chemical composition of aerosol particles and suggest several supervised algorithms for highly reliable automatic classification.