Closed editorialbot closed 7 months ago
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
Software report:
github.com/AlDanial/cloc v 1.88 T=0.13 s (822.4 files/s, 94431.4 lines/s)
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Language files blank comment code
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Python 59 1244 1575 5501
TeX 2 86 16 730
INI 4 14 0 376
reStructuredText 21 188 96 308
YAML 6 24 5 210
Markdown 5 78 0 183
Jupyter Notebook 5 0 1234 140
TOML 1 9 3 56
DOS Batch 1 10 1 39
make 1 6 11 18
CSS 1 1 0 9
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SUM: 106 1660 2941 7570
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gitinspector failed to run statistical information for the repository
Wordcount for paper.md
is 1580
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
OK DOIs
- 10.21105/joss.05428 is OK
- 10.1145/3544489 is OK
- 10.23915/distill.00026 is OK
- 10.21105/joss.00024 is OK
MISSING DOIs
- 10.1007/s10898-012-9951-y may be a valid DOI for title: Derivative-free optimization: a review of algorithms and comparison of software implementations
- 10.1109/tte.2022.3218341 may be a valid DOI for title: Topology Comparison and Sensitivity Analysis of Fuel Cell Hybrid Systems for Electric Vehicles
- 10.1016/j.petsci.2022.06.016 may be a valid DOI for title: Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm
- 10.1101/2021.03.11.434913 may be a valid DOI for title: On the generality and cognitive basis of base-rate neglect
- 10.1016/j.jmapro.2021.02.052 may be a valid DOI for title: A novel energy partition model for belt grinding of Inconel 718
- 10.1016/j.jeem.2020.102317 may be a valid DOI for title: The impact of wildfires on the recreational value of heathland: A discrete factor approach with adjustment for on-site sampling
- 10.1137/040603371 may be a valid DOI for title: Mesh Adaptive Direct Search Algorithms for Constrained Optimization
- 10.1109/wsc.2006.323088 may be a valid DOI for title: Adaptation of the UOBYQA algorithm for noisy functions
- 10.1137/080716980 may be a valid DOI for title: OrthoMADS: A deterministic MADS instance with orthogonal directions
- 10.1007/s10589-020-00249-0 may be a valid DOI for title: Stochastic mesh adaptive direct search for blackbox optimization using probabilistic estimates
- 10.1038/s41586-023-06124-2 may be a valid DOI for title: Expertise increases planning depth in human gameplay
- 10.1101/500413 may be a valid DOI for title: Causal inference in the multisensory brain
- 10.1038/s41593-019-0453-9 may be a valid DOI for title: Optimal policy for multi-alternative decisions
- 10.1038/s41562-019-0804-2 may be a valid DOI for title: Quantum reinforcement learning during human decision-making
- 10.1016/j.cub.2019.04.067 may be a valid DOI for title: Simple Acoustic Features Can Explain Phoneme-Based Predictions of Cortical Responses to Speech
- 10.1016/j.jmapro.2020.07.018 may be a valid DOI for title: A new method to achieve dynamic heat input monitoring in robotic belt grinding of Inconel 718
- 10.3390/en14030626 may be a valid DOI for title: Interpretation of Gas/Water Relative Permeability of Coal Using the Hybrid Bayesian-Assisted History Matching: New Insights
- 10.1109/jproc.2015.2494218 may be a valid DOI for title: Taking the Human Out of the Loop: A Review of Bayesian Optimization
- 10.1016/j.anucene.2020.108046 may be a valid DOI for title: Application of Kriging and Variational Bayesian Monte Carlo method for improved prediction of doped UO2 fission gas release
- 10.1007/s40857-022-00277-2 may be a valid DOI for title: Application of Dual-Source Modal Dispersion and Variational Bayesian Monte Carlo Method for Local Geoacoustic Inversion in Weakly Range-Dependent Shallow Water
- 10.3390/pharmaceutics14040749 may be a valid DOI for title: Interrogating and Quantifying In Vitro Cancer Drug Pharmacodynamics via Agent-Based and Bayesian Monte Carlo Modelling
- 10.1162/neco_a_01127 may be a valid DOI for title: Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions
- 10.1214/20-ba1200 may be a valid DOI for title: Parallel Gaussian Process Surrogate Bayesian Inference with Noisy Likelihood Evaluations
- 10.1016/0378-3758(91)90002-v may be a valid DOI for title: Bayes–Hermite quadrature
INVALID DOIs
- None
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Reviewers @max-little and @gaxler, please let me know if you have any questions about how to get started on your reviews!
@GurjeetSinghSangra, at some point be sure to address those missing DOI's that got flagged above.
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
@editorialbot check references
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
OK DOIs
- 10.1007/s10898-012-9951-y is OK
- 10.1109/TTE.2022.3218341 is OK
- 10.1016/j.petsci.2022.06.016 is OK
- 10.1101/2021.03.11.434913 is OK
- 10.1016/j.jmapro.2021.02.052 is OK
- 10.1016/j.jeem.2020.102317 is OK
- 10.1137/040603371 is OK
- 10.1109/wsc.2006.323088 is OK
- 10.1137/080716980 is OK
- 10.1007/s10589-020-00249-0 is OK
- 10.21105/joss.05428 is OK
- 10.1145/3544489 is OK
- 10.1038/s41586-023-06124-2 is OK
- 10.1016/j.neuron.2019.03.043 is OK
- 10.1038/s41593-019-0453-9 is OK
- 10.1038/s41562-019-0804-2 is OK
- 10.1016/j.cub.2019.04.067 is OK
- 10.1016/j.jmapro.2020.07.018 is OK
- 10.3390/en14030626 is OK
- 10.1109/JPROC.2015.2494218 is OK
- 10.23915/distill.00026 is OK
- 10.1016/j.anucene.2020.108046 is OK
- 10.1007/s40857-022-00277-2 is OK
- 10.3390/pharmaceutics14040749 is OK
- 10.1162/neco_a_01127 is OK
- 10.1214/20-ba1200 is OK
- 10.1016/0378-3758(91)90002-V is OK
- 10.21105/joss.00024 is OK
MISSING DOIs
- None
INVALID DOIs
- None
👋 Hi reviewers @max-little and @gaxler, just checking in again on this!
👋 Hi again @max-little and @gaxler, any updates on when you'll be able to start your reviews?
@max-little and @gaxler, are you still able to review this submission to JOSS?
Thanks for getting things started here, @gaxler! Checking in with @max-little again... 🔔
Sent an email to @max-little to check in; if I don't get a response in a few days I'll find a replacement reviewer.
(link to pre-review for my own reference here so I don't re-ask the same people who already said no: https://github.com/openjournals/joss-reviews/issues/5544 )
👋 @jungtaekkim, 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
Hi @rkurchin, I am willing to review this submission. Please add me as a reviewer.
@editorialbot add @jungtaekkim as reviewer
@jungtaekkim added to the reviewers list!
@jungtaekkim, let me know if you need any further guidance on how to get your review started! Take a look at the first comment in the issue for some initial information.
@gaxler and @jungtaekkim, checking in on review progress here! You should feel free to open issues etc. in the project repo as part of your review; if you do so, please link back to this issue for easy tracking.
Hi, pinging reviewers @gaxler and @jungtaekkim again!
@editorialbot remove @max-little as reviewer
@max-little removed from the reviewers list!
@rkurchin I am sorry for the delay. I will upload my review as soon as possible.
Checking in with reviewers @gaxler and @jungtaekkim – any sense when you'll be able to finish working through your checklists?
I left the review on the PyBADS codebase and the paper.
Please see the following issues:
I will update my checklist if they are resolved or answered.
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
@rkurchin I am sorry for the late review. My concerns and questions have been resolved, so I updated my checklist. Please let me know if there is a further step.
@editorialbot generate pdf
:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:
Thanks @jungtaekkim, if you're happy to recommend publication than we're all set there.
@gaxler, any updates on the rest of your review?
(Sent @gaxler an email to check in about review)
Dear editor @gaxler, I trust this message finds you well. We appreciate the time and effort invested by you and the reviewers thus far; however, it has come to our attention that one of the assigned reviewers has not responded or continued with the review process. We understand the busy schedule and work commitments of reviewers, nevertheless receiving feedback impacts our work and deadlines. We kindly ask for your assistance in prioritising and concluding the review process. We know that finding competent and reliable reviewers is a difficult task, and we truly appreciate your effort and collaboration. Thank you for your understanding and prompt attention to this matter. Best regards, Gurjeet
Hi @GurjeetSinghSangra, I'm the editor here – apologies for the troubles seeing this one through; it may not be much consolation, but this is the most dramatic case I've ever handled of reviewers ghosting mid-review. I will work on finding another reviewer for this submission ASAP!
@editorialbot remove @gaxler as reviewer
@gaxler removed from the reviewers list!
👋 @vankesteren and/or @tmigot, 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
Dear editor @rkurchin , unfortunately I am not available for the upcoming monthes, so I prefer to decline the invitation. Best, Tangi
👋 @sarats, 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
If we can help in any way to speed up the process please let us know @rkurchin, e.g. by proposing potential reviewers. Since it's been quite a while since our first submission, if a reviewer doesn't reply positively within a few days I'd suggest we move on with other reviewers until someone can take the task. Thanks for your support!
Sorry @rkurchin I'm presently on extended vacation, can't get this done in a timely manner and it won't be fair given the extensive delays incurred in this case already.
@lacerbi I'd certainly be open to other reviewer suggestions at this point!
Hello @rkurchin, I would like to suggest the following most relevant reviewers I found on the JOSS web-search.
I haven't tagged them, as I don't want to spam their emails all at once.
Hey @sgbaird, you were invited to review this one in pre-review and were bandwidth-constrained at the time, but as that was ~5 months ago and you seemed interested and clearly qualified, would you be willing to step in as a second reviewer here?
Submitting author: !--author-handle-->@GurjeetSinghSangra<!--end-author-handle-- (Gurjeet Singh) Repository: https://github.com/acerbilab/pybads Branch with paper.md (empty if default branch): joss-submission Version: 1.0.4 Editor: !--editor-->@rkurchin<!--end-editor-- Reviewers: @jungtaekkim, @vankesteren Archive: 10.5281/zenodo.10696782
Status
Status badge code:
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
@max-little & @gaxler, 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:
The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @rkurchin 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
📝 Checklist for @jungtaekkim
📝 Checklist for @vankesteren