[REVIEW]: Accelerated oblique random survival forests

[editorialbot]

Submitting author: @bcjaeger (Byron Jaeger)
Repository: https://github.com/bcjaeger/aorsf
Branch with paper.md (empty if default branch):
Version: v0.0.3
Editor: @danielskatz
Reviewers: @danielskatz
Archive: 10.5281/zenodo.7116855

Status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/414871f081cd8449007d671a7f7f7c3a"><img src="https://joss.theoj.org/papers/414871f081cd8449007d671a7f7f7c3a/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/414871f081cd8449007d671a7f7f7c3a/status.svg)](https://joss.theoj.org/papers/414871f081cd8449007d671a7f7f7c3a)

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.)

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

@danielskatz, please create your checklist typing: @editorialbot generate my checklist

[editorialbot]

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]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.09 s (914.8 files/s, 185191.5 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
R                               45           2138           2154           4583
C++                              2           1216            875           2124
XML                              1              0              2            441
Rmd                             17            634            548            379
Markdown                         6            126              0            315
JSON                             1              0              0            270
YAML                             7             45             20            226
TeX                              1             15              0             84
-------------------------------------------------------------------------------
SUM:                            80           4174           3599           8422
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 784

[editorialbot]

Failed to discover a Statement of need section in paper

[editorialbot]

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

OK DOIs

- 10.48550/ARXIV.2208.01129 is OK

MISSING DOIs

- 10.1007/978-3-030-56485-8_3 may be a valid DOI for title: Random forests
- 10.1214/19-aoas1261 may be a valid DOI for title: Oblique random survival forests
- 10.1161/circulationaha.120.053134 may be a valid DOI for title: Development and Validation of Machine Learning–Based Race-Specific Models to Predict 10-Year Risk of Heart Failure: A Multicohort Analysis
- 10.1016/j.patcog.2019.107078 may be a valid DOI for title: Heterogeneous oblique random forest

INVALID DOIs

- None

[editorialbot]

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

[danielskatz]

@bcjaeger - please add a statement of need section to the paper, and in that, or in the introduction, please explain more generally what this software does and what types of applications it has, remembering that JOSS has a very diverse readership, not all of which has detailed machine learning expertise. For example, the paper probably needs to explain what right-censored time-to-event data is and where it appears/is used, what survival decision trees are and where they appear/are used, what risk prediction models are and where they appear/are used, etc.

[danielskatz]

Also, is the "?" in this part of the text right?

[danielskatz]

Another issue: please address the possibly missing DOIs that editorialbot suggests, but note that some may be incorrect. Please feel free to make changes to your .bib file, then use the command @editorialbot check references to check again, and the command @editorialbot generate pdf when the references are right to make a new PDF. editorialbot commands need to be the first entry in a new comment.

[danielskatz]

And finally, for the first two references, please fix the cases of the journals to "Machine Learning" and "The Annals of Applied Statistics"

[bcjaeger]

Thanks! I will work on this now.

[bcjaeger]

@editorialbot check references

[editorialbot]

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

OK DOIs

- 10.1214/08-AOAS169 is OK
- 10.48550/ARXIV.2208.01129 is OK
- 10.1023/A:1010933404324 is OK
- 10.1214/19-AOAS1261 is OK
- 10.1161/circulationaha.120.053134 is OK
- 10.1016/j.patcog.2019.107078 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[bcjaeger]

@editorialbot generate pdf

[editorialbot]

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

[danielskatz]

Thanks - this looks good to me. I will also proofread this more carefully when you are ready - please let me know if that's now, and if not, when it is :)

[bcjaeger]

@danielskatz, thanks for the help today! Here is a list of updates based on your comments.

Please add a statement of need section to the paper

Done, see lines 23-28 of the updated draft.

in that, or in the introduction, please explain more generally what this software does and what types of applications it has, remembering that JOSS has a very diverse readership, not all of which has detailed machine learning expertise.

Good point. In the intro, I have added a general description of risk prediction (1st paragraph) and a summary of what aorsf does and what applications it has (second paragraph).

the paper probably needs to explain what right-censored time-to-event data is and where it appears/is used, what survival decision trees are and where they appear/are used, what risk prediction models are and where they appear/are used, etc.

Agreed. In the update, I've included

• what risk prediction is and where it is used (lines 7-14)
• what censored outcomes are (lines 45-50; they are used in risk prediction, defined earlier)
• what survival decision trees are is included on lines 51-54

The bibliography and DOIs should also be in order now.

[bcjaeger]

Thanks - this looks good to me. I will also proofread this more carefully when you are ready - please let me know if that's now, and if not, when it is :)

Thank you! I would like to read through it once more tonight. May I add a post here sometime this evening (about 5 hours from now) to let you know when I've finished?

[danielskatz]

sure!

[bcjaeger]

I think it is ready for your review. The only change I am considering is swapping the statement of need section with the background section so that the background section would come before the statement of need. This change may be helpful because the statement of need covers topics that are introduced in the background. I'm looking forward to hearing what you think.

[danielskatz]

@editorialbot recommend-accept

[editorialbot]

Attempting dry run of processing paper acceptance...

[editorialbot]

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

OK DOIs

- 10.1214/08-AOAS169 is OK
- 10.48550/ARXIV.2208.01129 is OK
- 10.1023/A:1010933404324 is OK
- 10.1214/19-AOAS1261 is OK
- 10.1161/circulationaha.120.053134 is OK
- 10.1016/j.patcog.2019.107078 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[editorialbot]

⚠️ Error preparing paper acceptance. The generated XML metadata file is invalid.

ID ref-menze2011oblique already defined

[danielskatz]

@bcjaeger - please check your bib file - it seems like there's a bib label (menze2011oblique) that's being used twice.

[bcjaeger]

Sorry about that, the duplicated label has been removed.

[danielskatz]

@editorialbot recommend-accept

[editorialbot]

Attempting dry run of processing paper acceptance...

[editorialbot]

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

OK DOIs

- 10.1214/08-AOAS169 is OK
- 10.48550/ARXIV.2208.01129 is OK
- 10.1023/A:1010933404324 is OK
- 10.1214/19-AOAS1261 is OK
- 10.1161/circulationaha.120.053134 is OK
- 10.1016/j.patcog.2019.107078 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[editorialbot]

👋 @openjournals/joss-eics, this paper is ready to be accepted and published.

Check final proof 👉📄 Download article

If the paper PDF and the deposit XML files look good in openjournals/joss-papers#3557, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

[bcjaeger]

Thanks! I can confirm the final proof of the pdf looks good on my end.

[danielskatz]

@bcjaeger - please update the zenodo metadata (which does not require a new deposit, version, or DOI) so that the title and authors match those of the paper

[bcjaeger]

Good catch - the title and author list on the zenodo release now match the paper.

[danielskatz]

@editorialbot accept

[editorialbot]

Doing it live! Attempting automated processing of paper acceptance...

[editorialbot]

🐦🐦🐦 👉 Tweet for this paper 👈 🐦🐦🐦

[editorialbot]

🚨🚨🚨 THIS IS NOT A DRILL, YOU HAVE JUST ACCEPTED A PAPER INTO JOSS! 🚨🚨🚨

Here's what you must now do:

0. Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.04705 joss-papers#3559
1. Wait a couple of minutes, then verify that the paper DOI resolves https://doi.org/10.21105/joss.04705
2. If everything looks good, then close this review issue.
3. Party like you just published a paper! 🎉🌈🦄💃👻🤘

Any issues? Notify your editorial technical team...

[danielskatz]

Congratulations to @bcjaeger (Byron Jaeger) and co-authors!!

[editorialbot]

🎉🎉🎉 Congratulations on your paper acceptance! 🎉🎉🎉

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[bcjaeger]

Thank you!!