Articles | Volume 21, issue 10
https://doi.org/10.5194/bg-21-2447-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.Using automated machine learning for the upscaling of gross primary productivity
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- Final revised paper (published on 24 May 2024)
- Preprint (discussion started on 31 Aug 2023)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on bg-2023-141', Anonymous Referee #1, 29 Sep 2023
- AC1: 'Reply on RC1', Max Gaber, 12 Nov 2023
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CC1: 'Comment on bg-2023-141', Jiangong Liu, 01 Oct 2023
- CC2: 'Reply on CC1', Jiangong Liu, 01 Oct 2023
- AC3: 'Reply on CC1', Max Gaber, 12 Nov 2023
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RC2: 'Comment on bg-2023-141', Anonymous Referee #2, 23 Oct 2023
- AC2: 'Reply on RC2', Max Gaber, 12 Nov 2023
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (20 Nov 2023) by Andrew Feldman
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AR by Max Gaber on behalf of the Authors (05 Feb 2024)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (14 Feb 2024) by Andrew Feldman
RR by Jiangong Liu (27 Feb 2024)
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RR by Anonymous Referee #1 (01 Mar 2024)
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RR by Anonymous Referee #2 (05 Mar 2024)
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ED: Publish subject to minor revisions (review by editor) (09 Mar 2024) by Andrew Feldman
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AR by Max Gaber on behalf of the Authors (23 Mar 2024)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (07 Apr 2024) by Andrew Feldman
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AR by Max Gaber on behalf of the Authors (08 Apr 2024)
Manuscript