editorialbot commented 7 months ago

Submitting author: !--author-handle-->@elindgren@lucydot<!--end-editor-- Reviewers: @Chronum94, @naik-aakash Archive: 10.5281/zenodo.10723374

Status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/701ba7ae234081b2a0369668005a8ade"><img src="https://joss.theoj.org/papers/701ba7ae234081b2a0369668005a8ade/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/701ba7ae234081b2a0369668005a8ade/status.svg)](https://joss.theoj.org/papers/701ba7ae234081b2a0369668005a8ade)

Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@Chronum94 & @naik-aakash, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review. First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @lucydot know.

✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @naik-aakash

📝 Checklist for @Chronum94

editorialbot commented 7 months ago

Hello humans, I'm @editorialbot, a robot that can help you with some common editorial tasks.

For a list of things I can do to help you, just type:

@editorialbot commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

@editorialbot generate pdf

editorialbot commented 7 months ago

Software report:

github.com/AlDanial/cloc v 1.88  T=0.18 s (388.0 files/s, 167598.5 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
C/C++ Header                     3             29             26          12680
Python                          32           1135           1363           5117
C++                              2            255            192           3224
XML                              1              0              0            589
TeX                              1             17              0            559
Jupyter Notebook                 8              0           2795            538
Markdown                         4             59              0            278
YAML                             1             16             18            121
HTML                             3              6              1             65
Dockerfile                       1              6              5             56
reStructuredText                 9             41             55             47
CSS                              1             11              8             38
SVG                              1              0              0             23
TOML                             1              0              0              3
-------------------------------------------------------------------------------
SUM:                            68           1575           4463          23338
-------------------------------------------------------------------------------

gitinspector failed to run statistical information for the repository

editorialbot commented 7 months ago

Wordcount for paper.md is 684

editorialbot commented 7 months ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1080/23746149.2022.2093129 is OK
- 10.1021/acs.chemrev.0c01111 is OK
- 10.1103/PhysRevB.104.104309 is OK
- 10.1088/1361-648X/ac462b is OK
- 10.1063/5.0106617 is OK
- 10.1103/PhysRevB.108.054312 is OK
- 10.48550/arXiv.2301.03497 is OK
- 10.1038/s42005-023-01297-8 is OK
- 10.1016/j.mtphys.2023.101066 is OK
- 10.1088/1361-648X/aa680e is OK
- 10.1002/adts.201800184 is OK
- 10.7566/JPSJ.92.012001 is OK
- 10.1088/1361-648X/acd831 is OK
- 10.48550/arXiv.2304.06978 is OK

MISSING DOIs

- None

INVALID DOIs

- None

editorialbot commented 7 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

naik-aakash commented 7 months ago

Review checklist for @naik-aakash

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://gitlab.com/materials-modeling/calorine?
[x] License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@elindgren) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

lucydot commented 7 months ago

@Chronum94, @naik-aakash - how are the reviews going? If you have any questions about the process, please ask. @Chronum94 your first reviewer task it to generate checklist (see info about this at the top of the thread).

naik-aakash commented 7 months ago

Hi @lucydot , I am still reviewing the examples and code functionalities demonstrated. So far going Well. Only a few more things to check from my end in this aspect. Then I will make a summary comment here.

Chronum94 commented 7 months ago

Review checklist for @Chronum94

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://gitlab.com/materials-modeling/calorine?
[x] License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@elindgren) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

Chronum94 commented 7 months ago

Hi @lucydot I expect to be done with the review by the end of this work week (US Eastern time).

naik-aakash commented 7 months ago

Hi @lucydot, I have finished with my review now. I feel the calorinepackage is a worthy addition to the ever-growing tools in the fields of computational chemistry, physics, and materials science. The Python interface for model construction and analysis will be helpful in creating workflows, for example, in packages like atomate2 with minimal further work. The code is sufficiently documented with many example use cases; this helps to get familiar with code functionalities quickly and get started right away with ease. I also used the tools provided to test other NEP models available using the example codes, and the code worked very well on these as well.

Thank you, @lucydot, for inviting me to review this code; I very much enjoyed reviewing this package and am seriously considering trying to do more experiments with this tool in the near future.

I have some minor suggestions and opened issues on the source code repository. Some of them have already been addressed by @elindgren very quickly.

Open question (package related)

While the submitting author @elindgren has made a substantial contribution to this code, the list of contributors on the repository has some more names; I could not figure out what exactly was their contribution from the repo and why they are not included on the paper. Maybe it is something the authors can clarify.

Open question (curiosity about NEP performance)

I am interested in knowing from the authors where NEP stands on the ladder among the recent MLIP potentials like CHGNet, MACE, and M3GNet for single and multicomponent systems. Any insights on these aspects would be great!
How hard would it be to build a universal NEP potential?

elindgren commented 7 months ago

Thank you for the review and the nice comments @naik-aakash! I'd be happy to answer your questions. :smile:

While the submitting author @elindgren has made a substantial contribution to this code, the list of contributors on the repository has some more names; I could not figure out what exactly was their contribution from the repo and why they are not included on the paper. Maybe it is something the authors can clarify.

Everyone who has made substantial contributions are on the paper. The exceptions are people who either made small contributions or had no long-term stake in the development, or asked not to be included as they felt they hadn't contributed sufficiently to be a co-author.

I am interested in knowing from the authors where NEP stands on the ladder among the recent MLIP potentials like CHGNet, MACE, and M3GNet for single and multicomponent systems. Any insights on these aspects would be great!

NEP is an approach that focuses on maximizing accuracy without sacrificing computational efficiency, and fares well against many other MLPs. See for instance this paper where we present and discuss the NEP approach in general, and this preprint where NEP is compared to SA-GPR for simulating IR and Raman spectra.

How hard would it be to build a universal NEP potential?

We have explored this question to some extent in our recent preprint where we develop a NEP for up to 16 elements, with applications in high-entropy alloys.

Hope this clarifies things!

Chronum94 commented 7 months ago

I'm done with the review. The package looks well-designed and quite good. It has a clear problem statement in mind and in design (to run and analyse NEP models) and the first-class support for the somewhat-de-facto standard of an ASE calculator is quite appealing in terms of barrier to entry. The supporting literature appears to be well-founded and the documentation is quite complete. The authors have put in sincere and long-term effort into the codebase, and both the code quality and documentation quality reflects this.

There are some minor changes that I have suggested to the tutorial in the documentation which are by no means exclusive suggestions but more just pointing out minor things that can be improved to make the package more accessible to a new user. They almost exclusively focus on making the code in the documentation more amenable to 'I copy-pasted it, I want it to run.'

The package works as intended (to the parts I can test on my own hardware, unfortunately not the GPUNEP calculator). I think with the minor changes to the documentation suggested in the issue linked above, or even a good-faith word to attend to the issues in a timely manner will make it okay from my side,

Other questions I had in mind have (very fortuitously) already been answered in the above response by @elindgren for which I thank the author (and @naik-aakash for asking the questions).

naik-aakash commented 7 months ago

Thank you for the review and the nice comments @naik-aakash! I'd be happy to answer your questions. 😄

While the submitting author @elindgren has made a substantial contribution to this code, the list of contributors on the repository has some more names; I could not figure out what exactly was their contribution from the repo and why they are not included on the paper. Maybe it is something the authors can clarify.

Everyone who has made substantial contributions are on the paper. The exceptions are people who either made small contributions or had no long-term stake in the development, or asked not to be included as they felt they hadn't contributed sufficiently to be a co-author.

I am interested in knowing from the authors where NEP stands on the ladder among the recent MLIP potentials like CHGNet, MACE, and M3GNet for single and multicomponent systems. Any insights on these aspects would be great!

NEP is an approach that focuses on maximizing accuracy without sacrificing computational efficiency, and fares well against many other MLPs. See for instance this paper where we present and discuss the NEP approach in general, and this preprint where NEP is compared to SA-GPR for simulating IR and Raman spectra.

How hard would it be to build a universal NEP potential?

We have explored this question to some extent in our recent preprint where we develop a NEP for up to 16 elements, with applications in high-entropy alloys.

Hope this clarifies things!

Thanks @elindgren ! It certainly does clarify things and will surely check out the sources shared 😃

elindgren commented 7 months ago

I'm done with the review. The package looks well-designed and quite good. It has a clear problem statement in mind and in design (to run and analyse NEP models) and the first-class support for the somewhat-de-facto standard of an ASE calculator is quite appealing in terms of barrier to entry. The supporting literature appears to be well-founded and the documentation is quite complete. The authors have put in sincere and long-term effort into the codebase, and both the code quality and documentation quality reflects this.

There are some minor changes that I have suggested to the tutorial in the documentation which are by no means exclusive suggestions but more just pointing out minor things that can be improved to make the package more accessible to a new user. They almost exclusively focus on making the code in the documentation more amenable to 'I copy-pasted it, I want it to run.'

The package works as intended (to the parts I can test on my own hardware, unfortunately not the GPUNEP calculator). I think with the minor changes to the documentation suggested in the issue linked above, or even a good-faith word to attend to the issues in a timely manner will make it okay from my side,

Other questions I had in mind have (very fortuitously) already been answered in the above response by @elindgren for which I thank the author (and @naik-aakash for asking the questions).

Thank you for the nice review and comments @Chronum94! I'm currently addressing yours as well as @naik-aakash s' suggestions for improvement, will let you know here once it is done.

elindgren commented 7 months ago

@naik-aakash @Chronum94 I've addressed your comments and suggestions in this MR.

@naik-aakash I've also added a sentence about modifying NEP models via calorine to the draft.

@editorialbot generate pdf

elindgren commented 7 months ago

@editorialbot generate pdf

editorialbot commented 7 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

lucydot commented 7 months ago

Excellent @elindgren !

And thank-you @naik-aakash and @Chronum94 for donating your expertise - and for enabling a thoughtful and timely review process :)

All checkboxes are ticked, and I can see the points raised have been addressed in latest MR, so we will proceed to the final stage.

I'll generate the post-review checklist - @elindgren please let me know when your items are complete.

lucydot commented 7 months ago

Post-Review Checklist for Editor and Authors

Additional Author Tasks After Review is Complete

Double check authors and affiliations (including ORCIDs)
Make a release of the software with the latest changes from the review and post the version number here. This is the version that will be used in the JOSS paper.
Archive the release on Zenodo/figshare/etc and post the DOI here.
Make sure that the title and author list (including ORCIDs) in the archive match those in the JOSS paper.
Make sure that the license listed for the archive is the same as the software license.

Editor Tasks Prior to Acceptance

[x] Read the text of the paper and offer comments/corrections (as either a list or a pull request)
[x] Check that the archive title, author list, version tag, and the license are correct
[x] Set archive DOI with @editorialbot set <DOI here> as archive
[x] Set version with @editorialbot set <version here> as version
[x] Double check rendering of paper with @editorialbot generate pdf
[x] Specifically check the references with @editorialbot check references and ask author(s) to update as needed
[x] Recommend acceptance with @editorialbot recommend-accept

lucydot commented 7 months ago

@editorialbot generate pdf

lucydot commented 7 months ago

@editorialbot check references

editorialbot commented 7 months ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1080/23746149.2022.2093129 is OK
- 10.1021/acs.chemrev.0c01111 is OK
- 10.1103/PhysRevB.104.104309 is OK
- 10.1088/1361-648X/ac462b is OK
- 10.1063/5.0106617 is OK
- 10.1103/PhysRevB.108.054312 is OK
- 10.48550/arXiv.2301.03497 is OK
- 10.1038/s42005-023-01297-8 is OK
- 10.1016/j.mtphys.2023.101066 is OK
- 10.1088/1361-648X/aa680e is OK
- 10.1002/adts.201800184 is OK
- 10.7566/JPSJ.92.012001 is OK
- 10.1088/1361-648X/acd831 is OK
- 10.48550/arXiv.2304.06978 is OK

MISSING DOIs

- None

INVALID DOIs

- None

editorialbot commented 7 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

elindgren commented 7 months ago

@editorialbot generate pdf

elindgren commented 7 months ago

@editorialbot check references

editorialbot commented 7 months ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1080/23746149.2022.2093129 is OK
- 10.1021/acs.chemrev.0c01111 is OK
- 10.1103/PhysRevB.104.104309 is OK
- 10.1088/1361-648X/ac462b is OK
- 10.1063/5.0106617 is OK
- 10.1103/PhysRevB.108.054312 is OK
- 10.1021/acs.jpcc.3c01542 is OK
- 10.1038/s42005-023-01297-8 is OK
- 10.1016/j.mtphys.2023.101066 is OK
- 10.1088/1361-648X/aa680e is OK
- 10.1002/adts.201800184 is OK
- 10.7566/JPSJ.92.012001 is OK
- 10.1088/1361-648X/acd831 is OK
- 10.1021/acsnano.3c09717 is OK

MISSING DOIs

- None

INVALID DOIs

- None

elindgren commented 7 months ago

Excellent @elindgren !

And thank-you @naik-aakash and @Chronum94 for donating your expertise - and for enabling a thoughtful and timely review process :)

All checkboxes are ticked, and I can see the points raised have been addressed in latest MR, so we will proceed to the final stage.

I'll generate the post-review checklist - @elindgren please let me know when your items are complete.

Great! Will do! I've checked the Orcids and updated two of the references in the paper which have gone from preprints to published articles. Will let you know here once we've made a new release including the latest MR.

editorialbot commented 7 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

elindgren commented 6 months ago

Hi @lucydot, we've merged the remaining issues and made a new release of calorine. The new version is 2.2, associated with the following Zenodo record: https://doi.org/10.5281/zenodo.10689789

I've checked that both the authors and licenses matches between the paper and the repository/zenodo record. I think that should be everything from our side, right?

elindgren commented 6 months ago

Hi @lucydot, we've merged the remaining issues and made a new release of calorine. The new version is 2.2, associated with the following Zenodo record: https://doi.org/10.5281/zenodo.10689789

I've checked that both the authors and licenses matches between the paper and the repository/zenodo record. I think that should be everything from our side, right?

There seems to be an issue with the recent release we made (version 2.2), I'll let you know here once it is resolved. So please don't mark version 2.2 as the one in the paper :rofl:

lucydot commented 6 months ago

Thanks for updates @elindgren - I'll hold off with my final checks until you let me know here the issue is resolved. You will also need to make update the Zenodo accordingly and give me the new doi.

elindgren commented 6 months ago

Hey @lucydot we've fixed the issue now. The new version of calorine is 2.2.1, which has the following Zenodo DOI: https://zenodo.org/records/10723374.

lucydot commented 6 months ago

@editorialbot set v2.2.1 as version

editorialbot commented 6 months ago

Done! version is now v2.2.1

lucydot commented 6 months ago

@editorialbot set 10.5281/zenodo.10723374 as archive

editorialbot commented 6 months ago

Done! archive is now 10.5281/zenodo.10723374

lucydot commented 6 months ago

@elindgren - I'm just reading through the archive. For the "citation" and "published in" detail it points to the GPUMD package (https://pubs.aip.org/aip/jcp/article-abstract/157/11/114801/2841888/GPUMD-A-package-for-constructing-accurate-machine). Is this an oversight or deliberate? My expectation would be this metadata is updated to back to JOSS once the JOSS paper is published (so the JOSS points to the Zenodo archive, and vice-verca).

lucydot commented 6 months ago

@editorialbot generate pdf

lucydot commented 6 months ago

@editorialbot check references

editorialbot commented 6 months ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1080/23746149.2022.2093129 is OK
- 10.1021/acs.chemrev.0c01111 is OK
- 10.1103/PhysRevB.104.104309 is OK
- 10.1088/1361-648X/ac462b is OK
- 10.1063/5.0106617 is OK
- 10.1103/PhysRevB.108.054312 is OK
- 10.1021/acs.jpcc.3c01542 is OK
- 10.1038/s42005-023-01297-8 is OK
- 10.1016/j.mtphys.2023.101066 is OK
- 10.1088/1361-648X/aa680e is OK
- 10.1002/adts.201800184 is OK
- 10.7566/JPSJ.92.012001 is OK
- 10.1088/1361-648X/acd831 is OK
- 10.1021/acsnano.3c09717 is OK

MISSING DOIs

- None

INVALID DOIs

- None

editorialbot commented 6 months ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

elindgren commented 6 months ago

@elindgren - I'm just reading through the archive. For the "citation" and "published in" detail it points to the GPUMD package (https://pubs.aip.org/aip/jcp/article-abstract/157/11/114801/2841888/GPUMD-A-package-for-constructing-accurate-machine). Is this an oversight or deliberate? My expectation would be this metadata is updated to back to JOSS once the JOSS paper is published (so the JOSS points to the Zenodo archive, and vice-verca).

Yes, the plan is to update the metadata to point to the JOSS as soon as we have a DOI here. 😊

lucydot commented 6 months ago

@editorialbot recommend-accept

editorialbot commented 6 months ago

Attempting dry run of processing paper acceptance...

editorialbot commented 6 months ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1080/23746149.2022.2093129 is OK
- 10.1021/acs.chemrev.0c01111 is OK
- 10.1103/PhysRevB.104.104309 is OK
- 10.1088/1361-648X/ac462b is OK
- 10.1063/5.0106617 is OK
- 10.1103/PhysRevB.108.054312 is OK
- 10.1021/acs.jpcc.3c01542 is OK
- 10.1038/s42005-023-01297-8 is OK
- 10.1016/j.mtphys.2023.101066 is OK
- 10.1088/1361-648X/aa680e is OK
- 10.1002/adts.201800184 is OK
- 10.7566/JPSJ.92.012001 is OK
- 10.1088/1361-648X/acd831 is OK
- 10.1021/acsnano.3c09717 is OK

MISSING DOIs

- No DOI given, and none found for title: PyNEP
- No DOI given, and none found for title: Gpyumd

INVALID DOIs

- None

editorialbot commented 6 months ago

:wave: @openjournals/pe-eics, this paper is ready to be accepted and published.

Check final proof :point_right::page_facing_up: Download article

If the paper PDF and the deposit XML files look good in https://github.com/openjournals/joss-papers/pull/5095, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

lucydot commented 6 months ago

I've just looked up the two titles PyNEP and Gpuymd flagged by editorialbot and cannot find DOI's associated with either project, so I do not think any adjustment needed to paper.

elindgren commented 6 months ago

I've just looked up the two titles PyNEP and Gpuymd flagged by editorialbot and cannot find DOI's associated with either project, so I do not think any adjustment needed to paper.

Alright, perfect! What is the next step? Is it you or I that run @ editorialbot accept (intentionally misspelt to not trigger the bot)?

lucydot commented 6 months ago

It's out of our hands now @elindgren - one of the editors-in-chief will do their final checks. You can sit back, relax and run a NEP calculation :)

openjournals / joss-reviews

[REVIEW]: calorine: A Python package for constructing and sampling neuroevolution potential models #6264

Status

Reviewer instructions & questions

Checklists

Review checklist for @naik-aakash

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

Review checklist for @Chronum94

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

Open question (package related)

Open question (curiosity about NEP performance)

Post-Review Checklist for Editor and Authors

Additional Author Tasks After Review is Complete

Editor Tasks Prior to Acceptance