Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[PRE REVIEW]: Country-specific calculation of potential forest area (PFA) #7866

Open
editorialbot opened this issue Mar 3, 2025 · 7 comments
Labels
pre-review Python TeX Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning

Comments

@editorialbot
Copy link
Collaborator

Submitting author: @tomkeH (Tomke Honkomp)
Repository: https://github.com/TI-Forest-Sector-Modelling/PFA
Branch with paper.md (empty if default branch): main_for_publication
Version: v1.0.0
Editor: Pending
Reviewers: Pending
Managing EiC: Chris Vernon

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/e4f9fea857727702aad8772d5dce6ff9"><img src="https://joss.theoj.org/papers/e4f9fea857727702aad8772d5dce6ff9/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/e4f9fea857727702aad8772d5dce6ff9/status.svg)](https://joss.theoj.org/papers/e4f9fea857727702aad8772d5dce6ff9)

Author instructions

Thanks for submitting your paper to JOSS @tomkeH. Currently, there isn't a JOSS editor assigned to your paper.

@tomkeH if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). You can search the list of people that have already agreed to review and may be suitable for this submission.

Editor instructions

The JOSS submission bot @editorialbot is here to help you find and assign reviewers and start the main review. To find out what @editorialbot can do for you type:

@editorialbot commands
@editorialbot editorialbot added pre-review Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning labels Mar 3, 2025
@editorialbot
Copy link
Collaborator Author

Hello human, 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
Copy link
Collaborator Author

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

✅ OK DOIs

- 10.7717/peerj.15593 is OK
- 10.1007/s10584-011-0148-z is OK
- 10.1038/s41558-024-02113-z is OK
- 10.1038/s41597-022-01632-8 is OK
- 10.1017/9781009157926.009 is OK

🟡 SKIP DOIs

- None

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

@editorialbot
Copy link
Collaborator Author

Software report:

github.com/AlDanial/cloc v 1.98  T=0.02 s (866.0 files/s, 90968.7 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          10            208            200            917
Markdown                         5             80              1            284
CSV                              1              0              0            176
YAML                             1             10             13             63
TOML                             1             10              0             62
TeX                              1             10              1             52
Text                             1              0              0             14
-------------------------------------------------------------------------------
SUM:                            20            318            215           1568
-------------------------------------------------------------------------------

Commit count by author:

    26	honkomp
     1	Julia-ta

@editorialbot
Copy link
Collaborator Author

Paper file info:

📄 Wordcount for paper.md is 904

✅ The paper includes a Statement of need section

@editorialbot
Copy link
Collaborator Author

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

@editorialbot
Copy link
Collaborator Author

License info:

🟡 License found: Other (Check here for OSI approval)

@editorialbot
Copy link
Collaborator Author

Five most similar historical JOSS papers:

wdpar: Interface to the World Database on Protected Areas
Submitting author: @jeffreyhanson
Handling editor: @martinfleis (Active)
Reviewers: @Jo-Schie, @DrMattG
Similarity score: 0.7051

PROFFASTpylot: Running PROFFAST with Python
Submitting author: @feldl
Handling editor: @rwegener2 (Active)
Reviewers: @usethedata, @simonom
Similarity score: 0.6943

Geodata-Harvester: A Python package to jumpstart geospatial data extraction and analysis
Submitting author: @sebhaan
Handling editor: @hugoledoux (Active)
Reviewers: @lukasbeuster, @martibosch
Similarity score: 0.6935

swisslandstats-geopy: Python tools for the land statistics datasets from the Swiss Federal Statistical Office
Submitting author: @martibosch
Handling editor: @leouieda (Retired)
Reviewers: @weikang9009, @darribas
Similarity score: 0.6918

pyam: a Python Package for the Analysis and Visualization of Models of the Interaction of Climate, Human, and Environmental Systems
Submitting author: @gidden
Handling editor: @lheagy (Retired)
Reviewers: @jtmiclat, @Chilipp
Similarity score: 0.6884

⚠️ 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.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
pre-review Python TeX Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning
Projects
None yet
Development

No branches or pull requests

1 participant