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[REVIEW]: gibbonNetR: an R Package for the Use of Convolutional Neural Networks and TransferLearning on Acoustic Data #7250

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editorialbot opened this issue Sep 20, 2024 · 10 comments
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HTML R review TeX Track: 2 (BCM) Biomedical Engineering, Biosciences, Chemistry, and Materials

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Submitting author: @DenaJGibbon (Dena Clink)
Repository: https://github.com/DenaJGibbon/gibbonNetR
Branch with paper.md (empty if default branch):
Version: 1.0.0
Editor: @faroit
Reviewers: @Desjonqu, @steffilazerte
Archive: Pending

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/40a9136ac136e187df2bbff0bb1afd11"><img src="https://joss.theoj.org/papers/40a9136ac136e187df2bbff0bb1afd11/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/40a9136ac136e187df2bbff0bb1afd11/status.svg)](https://joss.theoj.org/papers/40a9136ac136e187df2bbff0bb1afd11)

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.)

Reviewer instructions & questions

@Desjonqu & @steffilazerte, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

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

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

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

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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

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Software report:

github.com/AlDanial/cloc v 1.90  T=0.04 s (703.6 files/s, 157934.5 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
R                               19            477            840           2404
HTML                             1             88              5            805
TeX                              1             39              0            418
Markdown                         3            120              0            340
Rmd                              1             72             90            115
YAML                             1              1              4             18
-------------------------------------------------------------------------------
SUM:                            26            797            939           4100
-------------------------------------------------------------------------------

Commit count by author:

   107	DenaJGibbon
     4	Dena J. Clink

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Paper file info:

📄 Wordcount for paper.md is 1857

✅ The paper includes a Statement of need section

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License info:

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

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

✅ OK DOIs

- 10.1093/biosci/biy147 is OK
- 10.1111/2041-210X.13101 is OK
- 10.1016/j.ecolind.2015.02.023 is OK
- 10.1038/nature14539 is OK
- 10.1371/journal.pcbi.1010372 is OK
- 10.7717/peerj.13152 is OK
- 10.1371/journal.pone.0283396 is OK
- 10.18637/jss.v091.i01 is OK
- 10.18637/jss.v028.i05 is OK
- 10.1016/j.ecolind.2021.107419 is OK
- 10.5281/zenodo.4092393 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: AMMonitor: Remote monitoring of biodiversity in an...
- No DOI given, and none found for title: Python and R for the Modern Data Scientist
- No DOI given, and none found for title: PyTorch: An Imperative Style, High-Performance Dee...
- No DOI given, and none found for title: TensorFlow: Large-Scale Machine Learning on Hetero...
- No DOI given, and none found for title: reticulate: Interface to ’Python’
- No DOI given, and none found for title: luz: Higher Level ’API’ for ’torch’
- No DOI given, and none found for title: Deep Learning with PyTorch
- No DOI given, and none found for title: Deep Learning
- No DOI given, and none found for title: A survey on deep transfer learning
- No DOI given, and none found for title: A survey of transfer learning
- No DOI given, and none found for title: Convolutional networks for images, speech, and tim...
- No DOI given, and none found for title: Recent advances in convolutional neural networks
- No DOI given, and none found for title: Very deep convolutional networks for large-scale i...
- No DOI given, and none found for title: Characterizing soundscapes across diverse ecosyste...
- No DOI given, and none found for title: Caret package
- No DOI given, and none found for title: umap: Uniform Manifold Approximation and Projectio...
- No DOI given, and none found for title: soundClass: An automatic sound classification tool...

❌ MISSING DOIs

- 10.3389/fevo.2023.1071640 may be a valid DOI for title: A workflow for the automated detection and classif...
- 10.1080/09524622.2015.1133320 may be a valid DOI for title: Assessment of error rates in acoustic monitoring w...
- 10.1163/2214-8647_dnp_e612900 may be a valid DOI for title: Keras
- 10.1109/cvpr.2009.5206848 may be a valid DOI for title: Imagenet: A large-scale hierarchical image databas...
- 10.1201/9781003275923 may be a valid DOI for title: Deep Learning and Scientific Computing with R torc...
- 10.1145/3065386 may be a valid DOI for title: Imagenet classification with deep convolutional ne...
- 10.1109/cvpr.2016.90 may be a valid DOI for title: Deep residual learning for image recognition
- 10.1016/j.ecoinf.2023.102457 may be a valid DOI for title: Mel-frequency cepstral coefficients outperform emb...
- 10.1038/s41598-023-49989-z may be a valid DOI for title: Global birdsong embeddings enable superior transfe...
- 10.1371/journal.pone.0246564 may be a valid DOI for title: Not by the light of the moon: investigating circad...
- 10.1111/btp.13205 may be a valid DOI for title: Evidence for acoustic niche partitioning depends o...

❌ INVALID DOIs

- https://doi.org/10.1016/j.ecoinf.2022.101688 is INVALID because of 'https://doi.org/' prefix
- https://doi.org/10.1016/j.apacoust.2022.108939 is INVALID because of 'https://doi.org/' prefix
- https://doi.org/10.1016/j.ecoinf.2023.102457 is INVALID because of 'https://doi.org/' prefix

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

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faroit commented Oct 1, 2024

👋 @Desjonqu @steffilazerte thanks again for agreeing to review this submission. Let me know if you need any help starting the review process here.

One additional thing I would like to ask you is to not use this issue thread for discussions but instead open github issues on https://github.com/DenaJGibbon/gibbonNetR and link back to this thread here for easier reference.

Please complete your review in the next 4-5 weeks 🙏

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faroit commented Oct 16, 2024

@Desjonqu @steffilazerte can you please give us an update about the status of your review? Let me know if you need help or have further questions.

@steffilazerte
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Hi @faroit, Hi @DenaJGibbon, I have no update to report other than that this review is on my to-do list and will be done within the requested time frame. Thanks!

@Desjonqu
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Hi @faroit, same here. I'll be probably working on this on November 6-7th, I'll try earlier but not sure it will happen.

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