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  • Tree regeneration in models of forest dynamics: A key priority for further research

    Authors: Olalla Díaz‐Yáñez; Yannek Käber; Tim Anders; Friedrich Bohn; Kristin H. Braziunas; Josef Brůna; Rico Fischer; Samuel M. Fischer; Jessica Hetzer; Thomas Hickler et al.
    DOI: 10.1002/ecs2.4807
    Submitted by odiazyanez    
    Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper is fully reproducible; we provide the protocol that the different modelers used, the data produced from these models, the observed data, and the code to run the analysis that led to the results of the paper, figures, and text. I have not come across any other paper in forestry that is as fully reproducible as our paper, so it might also be a rare example in this field and hopefully a motivation to others to do so. Please notice that we do not provide the models that were used to run the simulations, as these are the results used (or data collection), but we do provide the data resulting from these simulations.

  • Optimizing the Use of Carbonate Standards to Minimize Uncertainties in Clumped Isotope Data

    Authors: Ilja J. Kocken, Inigo A. Müller, Martin Ziegler
    DOI: 10.1029/2019GC008545
    Submitted by japhir      

    Why should we attempt to reproduce this paper?

    Even though the approach in the paper focuses on a specific measurement (clumped isotopes) and how to optimize which and how many standards we use, I hope that the problem is general enough that insight can translate to any kind of measurement that relies on machine calibration. I've committed to writing a literate program (plain text interspersed with code chunks) to explain what is going on and to make the simulations one step at a time. I really hope that this is understandable to future collaborators and scientists in my field, but I have not had any code review internally and I also didn't receive any feedback on it from the reviewers. I would love to see if what in my mind represents "reproducible code" is actually reproducible, and to learn what I can improve for future projects!

  • The viewing angle in AGN SED models, a data-driven analysis

    Authors: Andrés Felipe Ramos Padilla, Lingyu Wang, Katarzyna Małek, Andreas Efstathiou, Guang Yang
    Submitted by aframosp    
      Mean reproducibility score:   9.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    Most of the material is available through Jupyter notebooks in GitHub, and it should be easy to reproduce with the help of Binder. With the notebooks, you could experiment with different parameters to the ones analyzed in the paper. It also contains a large dataset of physical parameters of galaxies analysed in this work. We expect this work to be easily reproducible in the steps described in the repository.

  • Investigation into the annotation of protocol sequencing steps in the sequence read archive

    Authors: Alnasir, Jamie, and Hugh P. Shanahan.
    Submitted by hub-admin  

    Why should we attempt to reproduce this paper?

    Metadata annotation is key to reproducibility in sequencing experiments. Reproducing this research using the scripts provided will also show the current level of annotation in years since 2015 when the paper was published.

    Tags: Python SQL
  • Dynamic redistribution of plasticity in a cerebellar spiking neural network reproducing an associative learning task perturbed by TMS

    Authors: Alberto Antonietti, Jessica Monaco, Egidio D'Angelo, Alessandra Pedrocchi, and Claudia Casellato
    Submitted by @_Aalph    

    Why should we attempt to reproduce this paper?

    Paper and codes+data have been published 4 years ago, will they still work? I always try to release data and codes to reproduce my papers, but I seldom receive feedback. It would be useful to have comments from a reproducers' team, in order to improve sharing for future research (I switched from MATLAB to Python already).

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