Closed editorialbot closed 6 months ago
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Software report:
github.com/AlDanial/cloc v 1.88 T=0.20 s (802.9 files/s, 247455.9 lines/s)
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JavaScript 13 4737 4760 17564
HTML 16 1014 48 9376
Python 103 2320 1188 4860
Markdown 9 589 0 1375
CSS 5 304 69 1291
TeX 1 20 0 164
YAML 5 19 27 106
reStructuredText 6 80 150 90
DOS Batch 1 8 1 26
TOML 1 5 1 24
make 1 4 7 9
INI 1 0 0 2
Bourne Shell 1 0 0 1
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SUM: 163 9100 6251 34888
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gitinspector failed to run statistical information for the repository
Wordcount for paper.md
is 2020
Failed to discover a Statement of need
section in paper
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
OK DOIs
- 10.1093/gji/ggad446 is OK
- 10.1088/1742-6596/1719/1/012102 is OK
- 10.1109/ICEC.1997.592270 is OK
- 10.1007/s00500-016-2474-6 is OK
MISSING DOIs
- 10.1007/978-3-319-31204-0_9 may be a valid DOI for title: Automating Biomedical Data Science Through Tree-Based Pipeline Optimization
INVALID DOIs
- None
Five most similar historical JOSS papers:
Quilë: C++ genetic algorithms scientific library
Submitting author: @ttarkowski
Handling editor: @vissarion (Active)
Reviewers: @mbarzegary, @acrlakshman
Similarity score: 0.8091
pyGOURGS - global optimization of n-ary tree representable problems using uniform random global search
Submitting author: @pySRURGS
Handling editor: @arokem (Retired)
Reviewers: @iljah, @nicoguaro
Similarity score: 0.8090
DEPP - Differential Evolution Parallel Program
Submitting author: @gbertoldo
Handling editor: @meg-simula (Retired)
Reviewers: @HaoZeke, @dham
Similarity score: 0.8087
GAIM: A C++ library for Genetic Algorithms and Island Models
Submitting author: @gdetor
Handling editor: @majensen (Active)
Reviewers: @sjvrijn, @sarats
Similarity score: 0.8062
dcgp: Differentiable Cartesian Genetic Programming made easy.
Submitting author: @darioizzo
Handling editor: @VivianePons (Retired)
Reviewers: @Ohjeah, @shah314
Similarity score: 0.7986
⚠️ 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.
@Freakwill – you mentioned an earlier paper in your submission notes. Could you please link to it here so I can better understand what the focus/content of the earlier paper was?
Hi @arfon, I have translated the article to English: text.md
PS: original paper: https://pan.baidu.com/s/1IiXkm7XEaipOZ_mEeFWVng?pwd=n3a4 This is the journal (in Chinese) link: http://www.comprg.com.cn/post_show.asp?id=12947
@Freakwill – you mentioned an earlier paper in your submission notes. Could you please link to it here so I can better understand what the focus/content of the earlier paper was?
Hi @Freakwill – I'm afraid we don't have a way to deal with non-English based submissions. Could you please provide some kind of translated artifact here for us to review? Thank you.
I translate the article to English. It was written about 3 years ago. In these three years, the program has been greatly redesigned. @arfon Thank you for reviewing my submission. What could I do to improve the progress of reviewing or just wait?
Hi @Freakwill – I'm afraid we don't have a way to deal with non-English based submissions. Could you please provide some kind of translated artifact here for us to review? Thank you.
@editorialbot generate pdf
@editorialbot generate pdf
@editorialbot check references
My name is now @editorialbot
@editorialbot check references
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
OK DOIs
- 10.1093/gji/ggad446 is OK
- 10.1088/1742-6596/1719/1/012102 is OK
- 10.1109/ICEC.1997.592270 is OK
- 10.1007/s00500-016-2474-6 is OK
MISSING DOIs
- 10.1007/978-3-319-31204-0_9 may be a valid DOI for title: Automating Biomedical Data Science Through Tree-Based Pipeline Optimization
INVALID DOIs
- None
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
OK DOIs
- 10.1007/978-3-319-31204-0_9 is OK
- 10.1093/gji/ggad446 is OK
- 10.1088/1742-6596/1719/1/012102 is OK
- 10.1109/ICEC.1997.592270 is OK
- 10.1007/s00500-016-2474-6 is OK
MISSING DOIs
- None
INVALID DOIs
- None
@editorialbot commands
Hello @Freakwill, here are the things you can ask me to do:
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@editorialbot list editors
# Check the references of the paper for missing DOIs
@editorialbot check references
# Perform checks on the repository
@editorialbot check repository
# Adds a checklist for the reviewer using this command
@editorialbot generate my checklist
# Set a value for branch
@editorialbot set joss-paper as branch
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@editorialbot check repository
Software report:
github.com/AlDanial/cloc v 1.88 T=0.24 s (736.3 files/s, 224301.8 lines/s)
-------------------------------------------------------------------------------
Language files blank comment code
-------------------------------------------------------------------------------
JavaScript 13 4737 4760 17564
HTML 17 1189 51 11082
Python 110 2487 1275 5172
Markdown 11 675 0 1529
CSS 5 304 69 1291
TeX 1 20 0 165
reStructuredText 7 99 190 108
YAML 5 19 27 106
DOS Batch 1 8 1 26
TOML 1 5 1 24
make 1 4 7 9
INI 1 0 0 2
Bourne Shell 1 0 0 1
-------------------------------------------------------------------------------
SUM: 174 9547 6381 37079
-------------------------------------------------------------------------------
gitinspector failed to run statistical information for the repository
Wordcount for paper.md
is 1992
@editorialbot check repository
Software report:
github.com/AlDanial/cloc v 1.88 T=0.25 s (709.7 files/s, 216252.9 lines/s)
-------------------------------------------------------------------------------
Language files blank comment code
-------------------------------------------------------------------------------
JavaScript 13 4737 4760 17564
HTML 17 1189 51 11082
Python 110 2489 1275 5181
Markdown 11 675 0 1528
CSS 5 304 69 1291
TeX 1 20 0 165
reStructuredText 7 99 190 108
YAML 5 19 27 106
DOS Batch 1 8 1 26
TOML 1 5 1 24
make 1 4 7 9
INI 1 0 0 2
Bourne Shell 1 0 0 1
-------------------------------------------------------------------------------
SUM: 174 9549 6381 37087
-------------------------------------------------------------------------------
gitinspector failed to run statistical information for the repository
Wordcount for paper.md
is 1926
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Five most similar historical JOSS papers:
pyGOURGS - global optimization of n-ary tree representable problems using uniform random global search
Submitting author: @pySRURGS
Handling editor: @arokem (Retired)
Reviewers: @iljah, @nicoguaro
Similarity score: 0.8047
DEPP - Differential Evolution Parallel Program
Submitting author: @gbertoldo
Handling editor: @meg-simula (Retired)
Reviewers: @HaoZeke, @dham
Similarity score: 0.7977
Quilë: C++ genetic algorithms scientific library
Submitting author: @ttarkowski
Handling editor: @vissarion (Active)
Reviewers: @mbarzegary, @acrlakshman
Similarity score: 0.7951
GAIM: A C++ library for Genetic Algorithms and Island Models
Submitting author: @gdetor
Handling editor: @majensen (Active)
Reviewers: @sjvrijn, @sarats
Similarity score: 0.7921
dcgp: Differentiable Cartesian Genetic Programming made easy.
Submitting author: @darioizzo
Handling editor: @VivianePons (Retired)
Reviewers: @Ohjeah, @shah314
Similarity score: 0.7846
⚠️ 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.
Author instructions
Thanks for submitting your paper to JOSS @Freakwill. Currently, there isn't a JOSS editor assigned to your paper.
@Freakwill 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.
I suggest the following potential reviewers: professoralkmin shah314 AlessandroPierro sjvrijn JJ benjamin-lee jmadera HaoZeke dham acrlakshman mbarzegary Ohjeah
and the authors: gbertoldo ttarkowski
@editorialbot check references
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
OK DOIs
- 10.1007/978-3-319-31204-0_9 is OK
- 10.1093/gji/ggad446 is OK
- 10.1088/1742-6596/1719/1/012102 is OK
- 10.1109/ICEC.1997.592270 is OK
- 10.1007/s00500-016-2474-6 is OK
MISSING DOIs
- None
INVALID DOIs
- None
@editorialbot generate my checklist
Checklists can only be created once the review has started in the review issue
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Five most similar historical JOSS papers:
DEPP - Differential Evolution Parallel Program
Submitting author: @gbertoldo
Handling editor: @meg-simula (Retired)
Reviewers: @HaoZeke, @dham
Similarity score: 0.8131
pyGOURGS - global optimization of n-ary tree representable problems using uniform random global search
Submitting author: @pySRURGS
Handling editor: @arokem (Retired)
Reviewers: @iljah, @nicoguaro
Similarity score: 0.8071
GAIM: A C++ library for Genetic Algorithms and Island Models
Submitting author: @gdetor
Handling editor: @majensen (Active)
Reviewers: @sjvrijn, @sarats
Similarity score: 0.8058
Quilë: C++ genetic algorithms scientific library
Submitting author: @ttarkowski
Handling editor: @vissarion (Active)
Reviewers: @mbarzegary, @acrlakshman
Similarity score: 0.8042
dcgp: Differentiable Cartesian Genetic Programming made easy.
Submitting author: @darioizzo
Handling editor: @VivianePons (Retired)
Reviewers: @Ohjeah, @shah314
Similarity score: 0.8021
⚠️ 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.
I translate the article to English. It was written about 3 years ago. In these three years, the program has been greatly redesigned.
Many thanks. Refactors/redesign of software doesn't necessarily mean a follow-on publication in JOSS would be permitted by us. Could you say more about what significant new capabilities have been added since the original release/publication, and what sorts of research challenges can be addressed by them?
I'm also curious to learn more about community use here. Does the original paper have many citations? Are people using this package for their research already?
I translate the article to English. It was written about 3 years ago. In these three years, the program has been greatly redesigned.
Many thanks. Refactors/redesign of software doesn't necessarily mean a follow-on publication in JOSS would be permitted by us. Could you say more about what significant new capabilities have been added since the original release/publication, and what sorts of research challenges can be addressed by them?
I'm also curious to learn more about community use here. Does the original paper have many citations? Are people using this package for their research already?
In addition to refactoring the original code, we have adopted algebraic programming more thoroughly, greatly improving scalability, and making it easy to any iterative simulation. It has a natural way to implement the multi-population genetic algorithms (even multi-multi-population), since we make use of the similar algebraic structures of the two. We have implemented a variety of intelligent algorithms, including quantum GA, PSO, DE; designed specialized chromosomes for special variables such as probability distributions and permutations; designed a caching system to accelerate computation; and initially implemented parallel computing, although currently limited to parallel computation of fitness. Combined with machine learning models, we provide scikit-learn-style APIs, such as the GAMLPRegressor
with the same APIs of MLPRegressor
, which implements the evoluationary neural network.
Currently, this package has not been officially applied to research. However, I have used it to solve real-world problems (such as movie scheduling). We have produced instructional videos to allow more people to understand this package. I am also persuading my colleagues to use this package.
The journal I published had little influence in itself; my papers also seemed to be cited by no one. That was my first attempt to let people know about my immature works.
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Five most similar historical JOSS papers:
pyGOURGS - global optimization of n-ary tree representable problems using uniform random global search
Submitting author: @pySRURGS
Handling editor: @arokem (Retired)
Reviewers: @iljah, @nicoguaro
Similarity score: 0.8089
DEPP - Differential Evolution Parallel Program
Submitting author: @gbertoldo
Handling editor: @meg-simula (Retired)
Reviewers: @HaoZeke, @dham
Similarity score: 0.8086
GAIM: A C++ library for Genetic Algorithms and Island Models
Submitting author: @gdetor
Handling editor: @majensen (Active)
Reviewers: @sjvrijn, @sarats
Similarity score: 0.8073
Quilë: C++ genetic algorithms scientific library
Submitting author: @ttarkowski
Handling editor: @vissarion (Active)
Reviewers: @mbarzegary, @acrlakshman
Similarity score: 0.8043
dcgp: Differentiable Cartesian Genetic Programming made easy.
Submitting author: @darioizzo
Handling editor: @VivianePons (Retired)
Reviewers: @Ohjeah, @shah314
Similarity score: 0.8017
⚠️ 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.
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Five most similar historical JOSS papers:
pyGOURGS - global optimization of n-ary tree representable problems using uniform random global search
Submitting author: @pySRURGS
Handling editor: @arokem (Retired)
Reviewers: @iljah, @nicoguaro
Similarity score: 0.8084
DEPP - Differential Evolution Parallel Program
Submitting author: @gbertoldo
Handling editor: @meg-simula (Retired)
Reviewers: @HaoZeke, @dham
Similarity score: 0.8081
GAIM: A C++ library for Genetic Algorithms and Island Models
Submitting author: @gdetor
Handling editor: @majensen (Active)
Reviewers: @sjvrijn, @sarats
Similarity score: 0.8061
Quilë: C++ genetic algorithms scientific library
Submitting author: @ttarkowski
Handling editor: @vissarion (Active)
Reviewers: @mbarzegary, @acrlakshman
Similarity score: 0.8039
dcgp: Differentiable Cartesian Genetic Programming made easy.
Submitting author: @darioizzo
Handling editor: @VivianePons (Retired)
Reviewers: @Ohjeah, @shah314
Similarity score: 0.8003
⚠️ 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.
In addition to refactoring the original code, we have adopted algebraic programming more thoroughly, greatly improving scalability, and making it easy to any iterative simulation. It has a natural way to implement the multi-population genetic algorithms (even multi-multi-population), since we make use of the similar algebraic structures of the two. We have implemented a variety of intelligent algorithms, including quantum GA, PSO, DE; designed specialized chromosomes for special variables such as probability distributions and permutations; designed a caching system to accelerate computation; and initially implemented parallel computing, although currently limited to parallel computation of fitness. Combined with machine learning models, we provide scikit-learn-style APIs, such as the GAMLPRegressor with the same APIs of MLPRegressor, which implements the evoluationary neural network.
OK, thanks for the additional information @Freakwill. Have all of these changes been made since the earlier paper was published?
In addition to refactoring the original code, we have adopted algebraic programming more thoroughly, greatly improving scalability, and making it easy to any iterative simulation. It has a natural way to implement the multi-population genetic algorithms (even multi-multi-population), since we make use of the similar algebraic structures of the two. We have implemented a variety of intelligent algorithms, including quantum GA, PSO, DE; designed specialized chromosomes for special variables such as probability distributions and permutations; designed a caching system to accelerate computation; and initially implemented parallel computing, although currently limited to parallel computation of fitness. Combined with machine learning models, we provide scikit-learn-style APIs, such as the GAMLPRegressor with the same APIs of MLPRegressor, which implements the evoluationary neural network.
OK, thanks for the additional information @Freakwill. Have all of these changes been made since the earlier paper was published?
Sure. GitHub records all commits.
Submitting author: !--author-handle-->@Freakwill<!--end-author-handle-- (Congwei Song) Repository: https://github.com/Freakwill/pyrimidine Branch with paper.md (empty if default branch): Version: v1.5.4 Editor: !--editor-->@boisgera<!--end-editor-- Reviewers: @mmore500, @sjvrijn Managing EiC: Arfon Smith
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Author instructions
Thanks for submitting your paper to JOSS @Freakwill. Currently, there isn't a JOSS editor assigned to your paper.
@Freakwill 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: