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  • Investigating the replicability of preclinical cancer biology

    Authors: Timothy M Errington, Maya Mathur, Courtney K Soderberg, Alexandria Denis, Nicole Perfito, Elizabeth Iorns, Brian A Nosek
    DOI: 10.7554/eLife.71601
    Submitted by samuelpawel      

    Why should we attempt to reproduce this paper?

    This papers represents an important milestone in meta-science, as it is one of the first large-scale replication projects outside the social sciences.

  • Droplet impact onto a spring-supported plate: analysis and simulations

    Authors: Michael J. Negus, Matthew R. Moore, James M. Oliver, Radu Cimpeanu
    DOI: https://doi.org/10.1007/s10665-021-10107-5
    Submitted by MNegus      
      Mean reproducibility score:   8.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    The direct numerical simulations (DNS) for this paper were conducted using Basilisk (http://basilisk.fr/). As Basilisk is a free software program written in C, it can be readily installed on any Linux machine, and it should be straightforward to then run the driver code to re-produce the DNS from this paper. Given this, the numerical solutions presented in this paper are a result of many high-fidelity simulations, which each took approximately 24 CPU hours running between 4 to 8 cores. Hence the difficulty in reproducing the results should mainly be in the amount of computational resources it would take, so HPC resources will be required. The DNS in this paper were used to validate the presented analytical solutions, as well as extend the results to a longer timescale. Reproducing these numerical results will build confidence in these results, ensuring that they are independent of the system architecture they were produced on.

  • Machine learning a model for RNA structure prediction

    Authors: Nicola Calonaci, Alisha Jones, Francesca Cuturello, Michael Sattler, Giovanni Bussi
    DOI: 10.1093/nargab/lqaa090
    Submitted by giovannibussi      

    Why should we attempt to reproduce this paper?

    The method is trained on the data that were available, but it is meant to be re-trainable as soon as new data are published. It would be great to be really sure that even someone else will be able to do it. In case we receive any feedback, we would be really happy to improve our Github repository so as to make the reproduction easier!

  • Explicit (but not implicit) environmentalist identity predicts pro-environmental behavior and policy preferences

    Authors: Brick, C., & Lai, C. K.
    DOI: 10.1016/j.jenvp.2018.07.003
    Submitted by hub-admin    
      Mean reproducibility score:   6.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    The results of the individual studies (4) could be interpreted in support for the hypothesis, but the meta-analysis suggested that implicit identification was not a useful predictor overall. This conclusion is an important goalpost for future work.