AI Article Synopsis

  • The article by Lee et al. (2019) discusses concerns about reproducibility in cognitive science research, especially regarding model-based approaches.
  • The authors emphasize that improving research practices is key to enhancing model robustness, while also advocating for transparent sharing of model specifications and their results.
  • They outline efforts within the Brain Imaging Data Structure community to create standards for sharing computational model structures and outputs to boost reproducibility.

Article Abstract

The Target Article by Lee et al. (2019) highlights the ways in which ongoing concerns about research reproducibility extend to model-based approaches in cognitive science. Whereas Lee et al. focus primarily on the importance of research practices to improve model robustness, we propose that the transparent sharing of model specifications, including their inputs and outputs, is also essential to improving the reproducibility of model-based analyses. We outline an ongoing effort (within the context of the Brain Imaging Data Structure community) to develop standards for the sharing of the structure of computational models and their outputs.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241435PMC
http://dx.doi.org/10.1007/s42113-019-00062-xDOI Listing

Publication Analysis

Top Keywords

standards sharing
8
computational models
8
sharing computational
4
models data
4
data target
4
target article
4
article lee
4
lee 2019
4
2019 highlights
4
highlights ways
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!