Articles | Volume 20, issue 4
https://doi.org/10.5194/bg-20-897-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.Spatiotemporal lagging of predictors improves machine learning estimates of atmosphere–forest CO2 exchange
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- Final revised paper (published on 02 Mar 2023)
- Preprint (discussion started on 11 May 2022)
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-2022-108', Anonymous Referee #1, 02 Jun 2022
- AC1: 'Reply on RC1', Matti Kämäräinen, 18 Aug 2022
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RC2: 'Comment on bg-2022-108', Anonymous Referee #2, 03 Jun 2022
- AC2: 'Reply on RC2', Matti Kämäräinen, 18 Aug 2022
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (24 Aug 2022) by Trevor Keenan
AR by Matti Kämäräinen on behalf of the Authors (18 Nov 2022)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (17 Dec 2022) by Trevor Keenan
RR by Anonymous Referee #1 (06 Jan 2023)
ED: Publish subject to technical corrections (08 Feb 2023) by Trevor Keenan
AR by Matti Kämäräinen on behalf of the Authors (15 Feb 2023)
Manuscript