Articles | Volume 19, issue 8
Biogeosciences, 19, 2095–2099, 2022
https://doi.org/10.5194/bg-19-2095-2022
Biogeosciences, 19, 2095–2099, 2022
https://doi.org/10.5194/bg-19-2095-2022
Technical note
19 Apr 2022
Technical note | 19 Apr 2022

Technical note: Incorporating expert domain knowledge into causal structure discovery workflows

Jarmo Mäkelä et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2021-231', Jakob Runge, 27 Sep 2021
    • AC1: 'Reply on RC1', Jarmo Mäkelä, 02 Dec 2021
  • RC2: 'Comment on bg-2021-231', Michele Ronco, 25 Oct 2021
    • AC2: 'Reply on RC2', Jarmo Mäkelä, 02 Dec 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (10 Dec 2021) by Sönke Zaehle
AR by Jarmo Mäkelä on behalf of the Authors (13 Jan 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to minor revisions (review by editor) (15 Feb 2022) by Sönke Zaehle
AR by Jarmo Mäkelä on behalf of the Authors (28 Feb 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (21 Mar 2022) by Sönke Zaehle
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Short summary
Causal structure discovery algorithms have been making headway into Earth system sciences, and they can be used to increase our understanding on biosphere–atmosphere interactions. In this paper we present a procedure on how to utilize prior knowledge of the domain experts together with these algorithms in order to find more robust causal structure models. We also demonstrate how to avoid pitfalls such as over-fitting and concept drift during this process.
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