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While I don't disagree with your definition of reproducibility, I want to point out that very few papers would satisfy that criteria, regardless of their use of a closed- vs open-source software.

Here is a recent example: Imperial College COVID-19 response team published an article[1] where they modeled different effects of non-pharmaceutical interventions, such as suppression and mitigation on the number of infected, deaths, etc. This is a very interesting result, but it's impossible to replicate their results in practice without contacting the authors, as their methodology is not enough to reproduce it.

While someone else[2] posted their own model that is very well documented and fully reproducible by anyone with a $230/year personal license.

While theoretically [1] is high science and [2] is not, in my own opinion [2] is better than [1]. I would love more science to be done and discussed that way. Ideally, using open-source software, but in practice, using Wolfram Language, in that case, is already good enough in my opinion.

PS. I'm not affiliated with Wolfram Research in any way.

[1] https://www.imperial.ac.uk/media/imperial-college/medicine/s...

[2] https://community.wolfram.com/groups/-/m/t/1901002



Making an exact copy of an experiment is the lwest level of reproducibility. In science , reproducibility means reproducing the results with different components (people, tools, methodology), showing robust Independence form potential confounders.




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