[PRE REVIEW]: Interactive Classification Metrics: An interactive graphical Python package for building robust intuition for classification model evaluation

[editorialbot]

Submitting author: !--author-handle-->@davhbrown<!--end-author-handle-- (David Brown) Repository: https://github.com/davhbrown/interactive_classification_metrics Branch with paper.md (empty if default branch): joss-paper Version: 0.2.2 Editor: Pending Reviewers: Pending Managing EiC: Chris Vernon

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=0.01 s (577.6 files/s, 101652.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                           4            111            109            835
Markdown                         2             36              0            181
TeX                              1             10              0             98
YAML                             1              1              4             23
-------------------------------------------------------------------------------
SUM:                             8            158            113           1137
-------------------------------------------------------------------------------

Commit count by author:

    47  David H. Brown

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 1345

✅ The paper includes a Statement of need section

[editorialbot]

License info:

✅ License found: MIT License (Valid open source OSI approved license)

[editorialbot]

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

✅ OK DOIs

- 10.1126/science.adg8538 is OK
- 10.1186/s13040-021-00244-z is OK
- 10.1186/s13040-023-00322-4 is OK
- 10.1016/j.patter.2023.100804 is OK
- 10.1016/S2589-7500(19)30123-2 is OK
- 10.1016/j.patter.2020.100141 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Occupational Outlook Handbook, Data Scientists
- No DOI given, and none found for title: The MCC-F1 curve: a performance evaluation techniq...
- No DOI given, and none found for title: State of Data Science and Machine Learning
- No DOI given, and none found for title: Evaluation: from precision, recall and F-measure t...

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

[editorialbot]

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

[editorialbot]

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[davhbrown]

5 potential reviewers based on their Topic Area matches (machine learning, visualization, data science) & Language match for Python

• Yaoxiang Li
• Federico Errica
• Roque Lopez
• Simon Mutch
• EtienneCmb

[davhbrown]

Adding this submission's other author @davidechicco to the conversation.

[crvernon]

@editorialbot query scope

:wave: @davhbrown and @davidechicco - I am going to run this by our larger editorial board for scope review based on its lower lines of code count to ensure this meets our substantial scholarly effort requirement. I'll be back in touch with a decision ASAP. Thanks!

[editorialbot]

Submission flagged for editorial review.

[davhbrown]

Thanks for the update! Please let me know if you need additional information.

[crvernon]

@editorialbot reject

👋 @davhbrown and @davidechicco - After further review with our larger editorial board we have decided that we must reject this submission due to it not meeting our substantial scholarly effort requirements per the following:

• Low lines of code count
• Not packaged in a way that facilitates testing and reuse per community standards

We wish you the best and thank you for submitting to JOSS.

[editorialbot]

Paper rejected.