[PRE REVIEW]: hetGP4cast: adventures in ecological forecasting

[editorialbot]

Submitting author: @maikeh7 (Maike Holthuijzen)
Repository: https://github.com/maikeh7/hetGP4cast
Branch with paper.md (empty if default branch):
Version: 1.0.0
Editor: Pending
Reviewers: Pending
Managing EiC: Kristen Thyng

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Software report:

github.com/AlDanial/cloc v 1.88  T=0.01 s (904.4 files/s, 146518.0 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
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TeX                              1             62              8            575
Markdown                         3            103              0            364
R                                6             92            181            356
Rmd                              1             39            116             25
YAML                             1              1              4             18
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SUM:                            12            297            309           1338
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gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 586

[editorialbot]

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

[editorialbot]

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

OK DOIs

- None

MISSING DOIs

- 10.1109/wsc.2008.4736089 may be a valid DOI for title: Stochastic kriging for simulation metamodeling
- 10.1080/20442041.2020.1816421 may be a valid DOI for title: Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting
- 10.1029/2019wr024922 may be a valid DOI for title: Process-guided deep learning predictions of lake water temperature
- 10.1016/j.watres.2020.116307 may be a valid DOI for title: Data assimilation in surface water quality modeling: A review
- 10.1007/s00521-020-05601-3 may be a valid DOI for title: Coupling artificial neural networks with the artificial bee colony algorithm for global calibration of hydrological models
- 10.1046/j.1466-822x.2001.00256.x may be a valid DOI for title: Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space
- 10.1016/j.csda.2012.05.023 may be a valid DOI for title: Calibration of computer models with multivariate output
- 10.5194/gmd-15-6709-2022 may be a valid DOI for title: LPJ-GUESS/LSMv1. 0: a next-generation land surface model with high ecological realism
- 10.1093/treephys/20.5-6.289 may be a valid DOI for title: Process-based models for forest ecosystem management: current state of the art and challenges for practical implementation
- 10.1029/2011wr011527 may be a valid DOI for title: Review of surrogate modeling in water resources
- 10.1111/j.1467-9868.2004.05304.x may be a valid DOI for title: Probabilistic sensitivity analysis of complex models: a Bayesian approach
- 10.1007/s00477-017-1470-4 may be a valid DOI for title: Comparison of polynomial chaos and Gaussian process surrogates for uncertainty quantification and correlation estimation of spatially distributed open-channel steady flows
- 10.1016/j.envsoft.2017.11.037 may be a valid DOI for title: Uncertainty analysis of a semi-distributed hydrologic model based on a Gaussian Process emulator
- 10.1029/2019wr026138 may be a valid DOI for title: A near-term iterative forecasting system successfully predicts reservoir hydrodynamics and partitions uncertainty in real time
- 10.1201/9781003143376-17 may be a valid DOI for title: Physics-Guided Architecture (PGA) of LSTM Models for Uncertainty Quantification in Lake Temperature Modeling
- 10.5194/gmd-12-473-2019 may be a valid DOI for title: A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)
- 10.1137/1.9781611976236.60 may be a valid DOI for title: Physics-guided architecture (pga) of neural networks for quantifying uncertainty in lake temperature modeling
- 10.1016/j.watres.2022.119100 may be a valid DOI for title: Gaussian process emulation of spatio-temporal outputs of a 2D inland flood model
- 10.1016/j.envsoft.2017.02.006 may be a valid DOI for title: Appraisal of data-driven and mechanistic emulators of nonlinear simulators: The case of hydrodynamic urban drainage models
- 10.1088/0266-5611/30/11/114007 may be a valid DOI for title: Learning about physical parameters: The importance of model discrepancy
- 10.1007/s13253-020-00401-7 may be a valid DOI for title: Vecchia approximations of Gaussian-process predictions
- 10.1016/j.csda.2022.107537 may be a valid DOI for title: Large-scale local surrogate modeling of stochastic simulation experiments
- 10.1137/20m1336254 may be a valid DOI for title: Sparse Cholesky Factorization by Kullback–Leibler Minimization
- 10.1080/00401706.2018.1437476 may be a valid DOI for title: Permutation and grouping methods for sharpening Gaussian process approximations
- 10.1214/19-sts755 may be a valid DOI for title: A general framework for Vecchia approximations of Gaussian processes
- 10.1111/j.1467-9868.2007.00633.x may be a valid DOI for title: Fixed rank kriging for very large spatial data sets
- 10.1007/s13253-022-00488-0 may be a valid DOI for title: Multi-scale Vecchia approximations of Gaussian processes
- 10.1111/j.2517-6161.1988.tb01729.x may be a valid DOI for title: Estimation and model identification for continuous spatial processes
- 10.1080/01621459.2015.1044091 may be a valid DOI for title: Hierarchical nearest-neighbor Gaussian process models for large geostatistical datasets
- 10.1214/11-aoas489 may be a valid DOI for title: Efficient emulators of computer experiments using compactly supported correlation functions, with an application to cosmology
- 10.1006/jmva.2001.2056 may be a valid DOI for title: Compactly supported correlation functions
- 10.1109/tnnls.2019.2957109 may be a valid DOI for title: When Gaussian process meets big data: A review of scalable GPs
- 10.1109/icdm.2009.82 may be a valid DOI for title: Kernel conditional quantile estimation via reduction revisited
- 10.1016/j.jmarsys.2007.07.004 may be a valid DOI for title: Bayesian calibration of mechanistic aquatic biogeochemical models and benefits for environmental management
- 10.1016/j.watres.2014.09.002 may be a valid DOI for title: First report of the successful operation of a side stream supersaturation hypolimnetic oxygenation system in a eutrophic, shallow reservoir
- 10.21236/ada454828 may be a valid DOI for title: Strictly proper scoring rules, prediction, and estimation
- 10.1175/waf-d-17-0023.1 may be a valid DOI for title: Performance of the new NCEP Global Ensemble Forecast System in a parallel experiment
- 10.1007/978-1-4471-0657-9_2 may be a valid DOI for title: Space and space-time modeling using process convolutions

INVALID DOIs

- None

[editorialbot]

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[kthyng]

Hi @maikeh7 and thanks for your submission. I am going to ask the editorial board to take a look to see if it passes the bar for Substantial scholarly effort based on having few relatively lines of code.

[kthyng]

@editorialbot query scope

[editorialbot]

Submission flagged for editorial review.

[maikeh7]

Hi Kristen, thank you for at least considering my submission. I look forward to hearing from you. Maike Holthuijzen, Ph.D Postdoctoral appointee at Sandia National Lab https://maikeholthuijzen.weebly.com/ Nothing in life is to be feared, it is only to be understood - Marie Curie

…

________________________________ From: Kristen Thyng ***@***.***> Sent: Monday, January 22, 2024 10:34 To: openjournals/joss-reviews ***@***.***> Cc: Maike Holthuijzen ***@***.***>; Mention ***@***.***> Subject: Re: [openjournals/joss-reviews] [PRE REVIEW]: hetGP4cast: adventures in ecological forecasting (Issue #6245) Hi @maikeh7<https://urldefense.com/v3/__https://github.com/maikeh7__;!!JYXjzlvb!kyN0C2SNOyHXh9L9upFuuWhIV0rABBgm6Rd8mv2fe69dY7NyNfIpMvTjaetoURWyoaBOdLJzvGS9Ysnw34bb4us0s2XOaJtY4bs$> and thanks for your submission. I am going to ask the editorial board to take a look to see if it passes the bar for Substantial scholarly effort<https://urldefense.com/v3/__https://joss.readthedocs.io/en/latest/submitting.html*substantial-scholarly-effort__;Iw!!JYXjzlvb!kyN0C2SNOyHXh9L9upFuuWhIV0rABBgm6Rd8mv2fe69dY7NyNfIpMvTjaetoURWyoaBOdLJzvGS9Ysnw34bb4us0s2XObiCyGU0$> based on having few relatively lines of code. — Reply to this email directly, view it on GitHub<https://urldefense.com/v3/__https://github.com/openjournals/joss-reviews/issues/6245*issuecomment-1904258074__;Iw!!JYXjzlvb!kyN0C2SNOyHXh9L9upFuuWhIV0rABBgm6Rd8mv2fe69dY7NyNfIpMvTjaetoURWyoaBOdLJzvGS9Ysnw34bb4us0s2XOy0Ezm0o$>, or unsubscribe<https://urldefense.com/v3/__https://github.com/notifications/unsubscribe-auth/ADITOLBA4A4CDVECFZ72XYTYP2BJPAVCNFSM6AAAAABCCOI6KSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTSMBUGI2TQMBXGQ__;!!JYXjzlvb!kyN0C2SNOyHXh9L9upFuuWhIV0rABBgm6Rd8mv2fe69dY7NyNfIpMvTjaetoURWyoaBOdLJzvGS9Ysnw34bb4us0s2XO3Bwt708$>. You are receiving this because you were mentioned.Message ID: ***@***.***>

[kthyng]

Hi @maikeh7 — unfortunately the editorial board has determined the package doesn't pass the bar for substantial scholarly effort. However, if you continue to develop and expand the package, you are welcome to submit again in the future. Thank you.

[kthyng]

@editorialbot reject

[editorialbot]

Paper rejected.