REMoDNaV: robust eye-movement classification for dynamic stimulation

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Submitted by adswa

Nov. 4, 2021, 12:09 p.m.

REMoDNaV: robust eye-movement classification for dynamic stimulation

Asim H. Dar, Adina S. Wagner, Michael Hanke
Dar, A.H., Wagner, A.S. & Hanke, M. REMoDNaV: robust eye-movement classification for dynamic stimulation. Behav Res 53, 399–414 (2021).

  Mean reproducibility score:   7.0/10   |   Number of reviews:   3

Brief Description
Our paper describes a Python-based validation of REMoDNaV, an open source algorithm for eye movement classification.
Its underlying data stems from three different datasets, the algorithm has been published as a Python package and the paper is written as a dynamically generated document, relying on LaTeX and Make.
Why should we reproduce your paper?
In theory, reproducing this paper should only require a clone of a public Git repository, and the execution of a Makefile (detailed in the README of the paper repository at We've set up our paper to be dynamically generated, retrieving and installing the relevant data and software automatically, and we've even created a tutorial about it, so that others can reuse the same setup for their work. Nevertheless, we've for example never tried it out across different operating systems - who knows whether it works on Windows? We'd love to share the tips and tricks we found to work, and even more love feedback on how to improve this further.
What should reviewers focus on?
Does this work out of the box for your operating system? Are the listed requirements in the README complete, or have we forgotten one? Can you recompute the numerical results, and the figures automatically?


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