[PRE REVIEW] Detection and attribution of climate change: A deep learning and variational approach

[acocac]

Notebook Pre-Review

Submitting author: @ancazugo @SkirOwen @ViktorDomazetoski

Repository: https://github.com/eds-book-gallery/CI2023-RC-team2

Paper: https://doi.org/10.1017/eds.2022.17

Editor: @ampersandmcd

Reviewer: @asthanameghna @NHomer-Edi @dbhatedin

Managing EiC: @acocac

Status

Author instructions

Thanks for submitting your notebook to EDS book.

Editor instructions

Thank you for considering managing the review workflow of a notebook submission to EDS book.

Please find and assign reviewers and start the main review.

[acocac]

@ampersandmcd thanks for confirming your availability to moderate the discussion for this submission, may I ask if you can assign reviewers and confirm their availability?

[acocac]

Hi @asthanameghna @NHomer-Edi @dbhatedin — you volunteered to review for the CI2023 Reproducibility Challenge co-hosted by EDS book, Climate Informatics and Cambridge University Press and Assessment. Could you take a look at this submission and let us know if you might be able to volunteer a review for us? Thanks!

[asthanameghna]

I can take it up

[NHomer-Edi]

I am happy to review - it looks like a very interesting paper!

[dbhatedin]

Yes, glad to review, the topic is so impactful.

[acocac]

Closing as all reviewers confirm their availability.