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  • Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA

    Authors: Sahil Loomba, Alexandre de Figueiredo, Simon J. Piatek, Kristen de Graaf, Heidi J. Larson
    DOI: 10.1038/s41562-021-01056-1
    Submitted by samuelpawel      
      Mean reproducibility score:   8.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    In the middle of the COVID-19 pandemic, this paper provided important evidence regarding the effect of misinformation on vaccination intent. Its analyses and conclusions were extremely important for decision makers. Therefore, it is also important that the analyses are reproducible.

  • 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.

  • Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling

    Authors: Sander van Rijn, Sebastian Schmitt, Matthijs van Leeuwen, Thomas Bäck
    Submitted by sjvrijn    
      Mean reproducibility score:   9.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    Because: - Two fellow PhDs working on different topics have been able to reproduce some figures by following the README instructions and I hope this extends to other people - I've tried to incorporate as many of the best practices as possible to make my code and data open and accessible - I've tried to make sure that my data is exactly reproducible with the specified random seed strategy - the paper suggests a method that should be useful to other researchers in my field, which is not useful unless my results are reproducible

  • pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage

    Authors: Bonaretti S, Gold GE, Beaupre GS
    DOI: 10.1371/journal.pone.0226501
    Submitted by hub-admin    
      Mean reproducibility score:   6.5/10   |   Number of reviews:   2
    Why should we attempt to reproduce this paper?

    The paper describes pyKNEEr, a python package for open and reproducible research on femoral knee cartilage using Jupyter notebooks as a user interface. I created this paper with the specific intent to make both the workflows it describes and the paper itself open and reproducible, following guidelines from authorities in the field. Therefore, two things in the paper can be reproduced: 1) workflow results: Table 2 contains links to all the Jupyter notebooks used to calculate the results. Computations are long and might require a server, so if you want to run them locally, I recommend using only 2 or 3 images as inputs for the computations. Also, the paper should be sufficient, but if you need further introductory info, there are a documentation website: https://sbonaretti.github.io/pyKNEEr/ and a "how to" video: https://youtu.be/7WPf5KFtYi8 2) paper graphs: In the captions of figures 1, 4, and 5 you can find links to data repository, code (a Jupyter notebook), and the computational environment (binder) to fully reproduce the graph. These computations can be easily run locally and require a few seconds. All Jupyter notebooks automatically download data from Zenodo and provide dependencies, which should make reproducibility easier.

  • Determination of the fundamental absorption and optical bandgap of dielectric thin films from single optical transmittance measurements

    Authors: A. Tejada, L. Montañez, C. Torres, P. Llontop, L. Flores-Escalante, F. De Zela, A. Winnacker, and J. A. Guerra
    Submitted by hub-admin    

    Why should we attempt to reproduce this paper?

    We propose a simple method to retrieve optical constants from single optical transmittance measurements, in particular in the fundamental absorption region. The construction of needed envelopes is arbitrary and will depend on the user. However, the method should still be robust and deliver similar results.

  • Algorithm configuration data mining for CMA evolution strategies

    Authors: Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck
    DOI: 10.1145/3071178.3071205
    Submitted by sjvrijn    
      Mean reproducibility score:   10.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    The original data took quite a while to produce for a previous paper, but for this paper, all tables and figures should be exactly reproducible by simply running the jupyter notebook.