[PRE REVIEW]: GrainLearning: A Bayesian uncertainty quantification toolbox for discrete and continuum numerical models of granular materials

[editorialbot]

Submitting author: @luisaforozco (Luisa Fernanda Orozco)
Repository: https://github.com/GrainLearning/grainLearning
Branch with paper.md (empty if default branch): joss_submission
Version: v2.0.2
Editor: @diehlpk
Reviewers: @gchure, @georgiastuart, @Haipeng-ustc
Managing EiC: Kevin M. Moerman

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Software report:

github.com/AlDanial/cloc v 1.88  T=0.12 s (657.8 files/s, 100347.3 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
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Python                          39           1232           1806           3772
YAML                            14             35             14            854
reStructuredText                10            409            689            514
Markdown                         7            140              2            386
Jupyter Notebook                 3              0           1688            174
TeX                              1              0              0            164
JSON                             1              0              0             45
TOML                             1              4              0             45
DOS Batch                        1              8              1             26
make                             1              4              7              9
Bourne Shell                     1              6             11              7
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SUM:                            79           1838           4218           5996
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gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 718

[editorialbot]

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

OK DOIs

- 10.1016/j.cma.2019.01.027 is OK
- 10.1007/s10035-017-0781-y is OK
- 10.1016/j.compgeo.2021.104491 is OK
- 10.1016/j.powtec.2021.11.044 is OK
- 10.1016/j.compgeo.2023.105957 is OK
- 10.23967/c.particles.2023.015 is OK
- 10.5281/zenodo.8352544 is OK
- 10.1016/J.APT.2018.03.001 is OK
- 10.1016/j.powtec.2011.03.023 is OK
- 10.1016/J.POWTEC.2021.07.048 is OK
- 10.1016/j.powtec.2016.01.003 is OK

MISSING DOIs

- None

INVALID DOIs

- https://doi.org/10.1016/j.cma.2023.116040 is INVALID because of 'https://doi.org/' prefix

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

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⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[Kevin-Mattheus-Moerman]

@editorialbot invite @diehlpk as editor

[editorialbot]

Invitation to edit this submission sent!

[diehlpk]

@editorialbot add @diehlpk as editor

[editorialbot]

Assigned! @diehlpk is now the editor

[diehlpk]

I can edit the paper, but can only start at the end of next week.

[luisaforozco]

Hello, other potential reviewers, from the list of JOSS reviewers:

• jwbuurlage
• a-ws-m
• gchure
• Haipeng-ustc
• georgiastuart
• prmiles

[diehlpk]

Hi @jwbuurlage do you have time to review that paper?

[diehlpk]

Hi @a-ws-m do you have time to review that paper?

[diehlpk]

Hi @prmiles do you have time to review this paper?

[diehlpk]

Hi @gchure do you have time to review this paper?

[diehlpk]

Hi @Haipeng-ustc do you have time to review this paper?

[diehlpk]

Hi @georgiastuart do you have time to review this paper?

[georgiastuart]

I think I can review in a week or two.

[gchure]

Hi @diehlpk, happy to review, though it may be two weeks to complete.

[diehlpk]

@editorialbot add @gchure as reviewer

[editorialbot]

@gchure added to the reviewers list!

[diehlpk]

@editorialbot add @georgiastuart as reviewer

[editorialbot]

@georgiastuart added to the reviewers list!

[diehlpk]

@editorialbot start review

[editorialbot]

OK, I've started the review over in #6338.

[Haipeng-ustc]

I'm happy to be one of the reviewers. It'll take me around two weeks to finish it.

[diehlpk]

@editorialbot add @Haipeng-ustc as reviewer

[editorialbot]

@Haipeng-ustc added to the reviewers list!

[Haipeng-ustc]

In my review of this repo, I found it is a well-developed software. The installation process works smoothly, although I didn't test on Windows. The code quality is good, and the tutorial provided makes it accessible to its users. Furthermore, the unit test suite is very developed as well. Overall, "GrainLearning" represents a decent package for its related research. I recommend it highly for its utility and design.

[diehlpk]

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[diehlpk]

In my review of this repo, I found it is a well-developed software. The installation process works smoothly, although I didn't test on Windows. The code quality is good, and the tutorial provided makes it accessible to its users. Furthermore, the unit test suite is very developed as well. Overall, "GrainLearning" represents a decent package for its related research. I recommend it highly for its utility and design.

@Haipeng-ustc could you please run @editorialbot generate my checklist and check the appropriate boxes?

[Haipeng-ustc]

@editorialbot generate my checklist

[editorialbot]

Checklists can only be created once the review has started in the review issue