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[REVIEW] Detection and attribution of climate change: A deep learning and variational approach #173
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The report below counts blank lines, comment lines, and physical lines of source code files using cloc. It was generated according to the latest commit 0b0ee44 of the Reviewers and authors feel free this info only for informative purposes. We will generate a similar report after the review process.
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👋 @asthanameghna @NHomer-Edi @dbhatedin we will conduct the review in this issue. Please read through the above information and let me know if you have any questions about the review process. Thank you 🙏 |
Hi @asthanameghna @NHomer-Edi @dbhatedin! How are you doing? Is everything OK with the review? Please let us know here when it's ready, then we'll suggest authors to go through each of your comments. |
Hi @acocac, my comments are ready to be sent to the authors :) |
My comment are ready too. I agree with all the comments by @NHomer-Edi. I am happy for the particiants to see the comments. |
Hi reviewer team! Happy to share with the participants, my comments are here: "Its a very in-depth work with several innovative constructs in AI being applied at critical points being the main strength of this work. My comments are more towards the layout of the available materials - like finally the data is put up in GitLab (and code as well but thats there in github as well) which could be seen in data fetch sub-section and from the published paper's ending list. Would be great to have the data in someplace like Zenodo or OpenAire.eu. So the published paper becomes very important, a primary go to for anybody wanting to know the data being run in the code. It would be very helpful if we can see some comments in the code as well pointing to the charts, graphs and their labels. Currently some graphs are appearing towards the bottom of the notebook run without any comments, and one has to compare with the paper to properly understand. One last comment is to state the impact in a few lines, as to make a statement on what would be missing if such AI techniques were not used. In the conclusion section in the paper future work has been mentioned but the impact part would be good to add in some section." |
@NHomer-Edi @asthanameghna @dbhatedin thanks for going through the checklist and provide feedback of the notebook repository. @ancazugo @SkirOwen @ViktorDomazetoski please go through reviewers' comments and address their suggestions if relevant to have the updated version of the notebook. Note the specific comments are available in the PR of the notebook repository (see here). |
@ancazugo @SkirOwen @ViktorDomazetoski may I ask your attention on above general comments left by reviewers? A reminder you can find their specific comments here. Please let me know if you have any questions, I'm happy to help. |
@ancazugo @SkirOwen @ViktorDomazetoski I just went through the reviewer's comments and see that a few of them are still pending. The notebook is really great and it would be really nice to publish it as soon as possible. Any plans to finalise it? I am happy to help if needed. Thanks, |
Dear Anne,
Thank you for your email!
About one month ago I created a new branch on the repo called Notebook-Final in which I had implemented (hopefully) all of the changes, but I didn't know I also needed to respond to the reviewer's comments. Once I arrive home from work today, I will also complete that.
Once that is done is there anything else that I can do to speed up the notebook publishing process?
Best regards,
Viktor
…________________________________
From: Anne Fouilloux ***@***.***>
Sent: Thursday, August 17, 2023 2:03 PM
To: alan-turing-institute/environmental-ds-book ***@***.***>
Cc: Viktor Domazetoski ***@***.***>; Mention ***@***.***>
Subject: Re: [alan-turing-institute/environmental-ds-book] [REVIEW] Detection and attribution of climate change: A deep learning and variational approach (Issue #173)
@ancazugo<https://github.com/ancazugo> @SkirOwen<https://github.com/SkirOwen> @ViktorDomazetoski<https://github.com/ViktorDomazetoski> I just went through the reviewer's comments and see that a few of them are still pending. The notebook is really great and it would be really nice to publish it as soon as possible. Any plans to finalise it? I am happy to help if needed. Thanks,
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Reply to this email directly, view it on GitHub<#173 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AYHCIZGWGO5I6E4TOYWQ5GTXVYCATANCNFSM6AAAAAAYNEQWLI>.
You are receiving this because you were mentioned.Message ID: ***@***.***>
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@ViktorDomazetoski You did a very good job! Sorry I forgot I had to check another branch for the notebook. I went through all the comments and check the updated notebook. You implemented all the requested changes. It is great! There is a comment on plots that could be replaced by interactive plots: I think we can keep the plots as they are and think about adding interactivity in a future version of the notebook (which could be done by anyone interested by interactive visualisation). From my side, the notebook is ready to be published. Thanks again for your hard work! |
👋 @ancazugo @SkirOwen @ViktorDomazetoski Congratulations! Your notebook submitted to 2023 CI Reproducibility Challenge is published! 🎉 We'll announce the release among EDS book social networks between today Monday 11th and tomorrow Tuesday 12th September. Finally, big thanks to our editor: @annefou and the reviewers: @asthanameghna @NHomer-Edi @dbhatedin — your inputs were valuable to improving the quality of the submission 🙏 |
Thanks a lot for all your hard work Alejandro, as well as @annefou<https://github.com/annefou>, @asthanameghna<https://github.com/asthanameghna>, @NHomer-Edi<https://github.com/NHomer-Edi>, @dbhatedin<https://github.com/dbhatedin>. It was a pleasure doing the challenge and collaborating with you.
Would love to stay in touch and collaborate again sometime!
Best regards,
Viktor
…________________________________
From: Alejandro © ***@***.***>
Sent: Monday, September 11, 2023 10:12 AM
To: alan-turing-institute/environmental-ds-book ***@***.***>
Cc: Viktor Domazetoski ***@***.***>; Mention ***@***.***>
Subject: Re: [alan-turing-institute/environmental-ds-book] [REVIEW] Detection and attribution of climate change: A deep learning and variational approach (Issue #173)
👋 @ancazugo<https://github.com/ancazugo> @SkirOwen<https://github.com/SkirOwen> @ViktorDomazetoski<https://github.com/ViktorDomazetoski>
Congratulations! Your notebook submitted to 2023 CI Reproducibility Challenge is published! 🎉 We'll announce the release among EDS book social networks between today Monday 11th and tomorrow Tuesday 12th September.
Finally, big thanks to our editor: @annefou<https://github.com/annefou> and the reviewers: @asthanameghna<https://github.com/asthanameghna> @NHomer-Edi<https://github.com/NHomer-Edi> @dbhatedin<https://github.com/dbhatedin> — your inputs were valuable to improving the quality of the submission 🙏
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Reply to this email directly, view it on GitHub<#173 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AYHCIZAMFMPDCSDHSO37NC3XZ3BXVANCNFSM6AAAAAAYNEQWLI>.
You are receiving this because you were mentioned.Message ID: ***@***.***>
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Notebook Review: Issue #171
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 @annefou
Reviewer: @asthanameghna @NHomer-Edi @dbhatedin
Managing EiC: @acocac
Status
Reviewer instructions & questions
Hi 👋 @asthanameghna @NHomer-Edi @dbhatedin, please carry out your review in this issue by updating the checklist below.
As a reviewer, you contribute to the technical quality of the content published by our community.
Before the review, EiC checked if the submission fits the minimum requirements.
The quality of the proposed contribution can be assessed through scientific, technical and code criteria.
The reviewer guidelines are available here: https://edsbook.org/publishing/guidelines/guidelines-reviewers.html.
Any questions/concerns please let @ampersandmcd know.
Review checklist for @asthanameghna
Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide.
Conflict of interest
Code of conduct an peer-review principles
General checks
notebook.ipynb
) part of the notebook repository?Reproducibility
Pedagogy
Ethical
Other Requirements
Final approval (post-review)
Review checklist for @NHomer-Edi
Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide.
Conflict of interest
Code of conduct an peer-review principles
General checks
notebook.ipynb
) part of the notebook repository?Reproducibility
Pedagogy
Ethical
Other Requirements
Final approval (post-review)
Review checklist for @dbhatedin
Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide.
Conflict of interest
Code of conduct an peer-review principles
General checks
notebook.ipynb
) part of the notebook repository?Reproducibility
Pedagogy
Ethical
Other Requirements
Final approval (post-review)
Additional instructions
Reviewer general comments are welcome on this REVIEW issue or directly to the notebook repository.
If you do the latter, you will find a Pull Request titled REVIEW where you can carry out the discussion with authors through ReviewNB, a third-party plugin in GitHub for displaying and commenting Jupyter Notebooks (see further details here).
In addition to ReviewNB, we suggest to explore or run the notebook in:
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