[PRE REVIEW]: cblearn: Comparison-based Machine Learning in Python

[editorialbot]

Submitting author: @dekuenstle (David-Elias Künstle)
Repository: https://github.com/cblearn/cblearn
Branch with paper.md (empty if default branch): joss
Version: v0.1.2
Editor: @mbarzegary
Reviewers: @haniyeka, @sherbold, @stsievert
Managing EiC: Arfon Smith

Status

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.12 s (740.0 files/s, 82464.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          59           1413           2777           3771
TeX                              1             32              2            372
reStructuredText                14            213            166            351
Markdown                         4             77              0            246
YAML                             5             14             25            163
DOS Batch                        1              8              1             26
TOML                             1              1              0             11
make                             1              4              7              9
INI                              1              0              0              6
-------------------------------------------------------------------------------
SUM:                            87           1762           2978           4955
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1277

[editorialbot]

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

OK DOIs

- 10.48550/arXiv.1912.01666 is OK
- 10.1167/jov.22.14.3985 is OK
- 10.1167/jov.22.13.5 is OK
- 10.1167/jov.22.14.3232 is OK
- 10.1109/MLSP.2012.6349720 is OK
- 10.1167/3.8.5 is OK
- 10.1145/1559755.1559760 is OK
- 10.1167/17.1.37 is OK
- 10.1167/jov.20.4.19 is OK
- 10.1167/jov.20.9.14 is OK
- 10.1167/12.3.19 is OK
- 10.1038/s41562-020-00951-3 is OK
- 10.3758/s13428-019-01285-3 is OK
- 10.1109/TVCG.2014.2346978 is OK
- 10.1145/3380741 is OK
- 10.48550/arXiv.1309.0238 is OK
- 10.1038/s41586-020-2649-2 is OK
- 10.21105/joss.04517 is OK
- 10.48550/arXiv.1511.02254 is OK
- 10.1167/jov.23.9.5388 is OK
- 10.48550/arXiv.2211.16459 is OK

MISSING DOIs

- 10.1109/cvpr46437.2021.00355 may be a valid DOI for title: Enriching ImageNet with Human Similarity Judgments and Psychological Embeddings
- 10.1609/hcomp.v1i1.13079 may be a valid DOI for title: The crowd-median algorithm
- 10.1109/icassp.2018.8461868 may be a valid DOI for title: The landscape of non-convex quadratic feasibility

INVALID DOIs

- None

[editorialbot]

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

[editorialbot]

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[arfon]

@dekuenstle - thanks for your submission to JOSS. We're currently managing a large backlog of submissions and the editor most appropriate for your area is already rather busy.

For now, we will need to waitlist this paper and process it as the queue reduces. Thanks for your patience!

[arfon]

@editorialbot invite @mbarzegary as editor

👋 @mbarzegary – would you be willing to edit this submission for JOSS?

[editorialbot]

Invitation to edit this submission sent!

[mbarzegary]

Hi @arfon
Yes, I can handle this.

[mbarzegary]

@editorialbot assign me as editor

[editorialbot]

Assigned! @mbarzegary is now the editor

[mbarzegary]

Hi @haniyeka 👋
Considering your field of expertise, would you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

Paper: https://raw.githubusercontent.com/openjournals/joss-papers/joss.05896/joss.05896/10.21105.joss.05896.pdf
Software: https://github.com/cblearn/cblearn

[mbarzegary]

Hi @ulf1 @sherbold @stsievert 👋
Considering that you have already published your software in JOSS, would any of you be willing to review this submission for JOSS? As you know, we carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

Paper: https://raw.githubusercontent.com/openjournals/joss-papers/joss.05896/joss.05896/10.21105.joss.05896.pdf
Software: https://github.com/cblearn/cblearn

[haniyeka]

Hi @mbarzegary,

Thank you for considering me to review this submission.
Yes, I can do that.

[sherbold]

Hi @mbarzegary

While I am generally available as reviewer for JOSS, my schedule is brutal for the rest of this year. If a review in the first half of January is okay, then yes, otherwise I unfortunately need to decline.

[stsievert]

I'd be happy to review this software. Thanks for the notification.

[mbarzegary]

Thank you @haniyeka @sherbold @stsievert

@sherbold yes, a review in the first half of January is fine.

[mbarzegary]

@editorialbot add @haniyeka as reviewer

[editorialbot]

@haniyeka added to the reviewers list!

[mbarzegary]

@editorialbot add @sherbold as reviewer

[editorialbot]

@sherbold added to the reviewers list!

[mbarzegary]

@editorialbot add @stsievert as reviewer

[editorialbot]

@stsievert added to the reviewers list!

[mbarzegary]

@editorialbot start review

[editorialbot]

OK, I've started the review over in #6139.