425 results found
    1. Human Biology and Medicine

    Science Forum: An open investigation of the reproducibility of cancer biology research

    Timothy M Errington et al.
    The Reproducibility Project: Cancer Biology will generate a high-quality dataset to explore questions about the reproducibility of research, and will make all data, analysis and other research materials openly available to the research community.
    1. Cancer Biology

    Replication Study: The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors

    Stephen K Horrigan, Reproducibility Project: Cancer Biology
    Editors' Summary: The results in this Replication Study could not be interpreted.
    1. Human Biology and Medicine

    Reproducibility Project: Cancer Biology: Time to do something about reproducibility

    Sean J Morrison
    Individual scientists, scientific communities and scientific journals can do more to assess the publication of irreproducible results, to promote good science, and to increase the efficiency with which the scientific community self-corrects.
    Editorial
    Available as:
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  1. Media coverage: First results of cancer reproducibility project released

    The Reproducibility Project: Cancer Biology aims to assess reproducibility in cancer biology and identify what influences its success or failure in science more generally.
    1. Cancer Biology

    Reproducibility in Cancer Biology: Making sense of replications

    Brian A Nosek, Timothy M Errington
    The first results from the Reproducibility Project: Cancer Biology suggest that there is scope for improving reproducibility in pre-clinical cancer research.
    1. Cancer Biology
    Reproducibility Project

    Reproducibility Project: Cancer Biology

    Curated by Roger Davis et al.
    Investigating reproducibility in preclinical cancer research.
  2. Robots work on the underbody sealing of a 2015 Chrysler 200 inside the paint shop at Chrysler Group’s Assembly Plant

    Reproducibility: automated.

    Repurposing continuous integration tools for scientific analyses takes the headache out of reproducible research.

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