> Every result is instantly reproducible. When you read a paper claiming that a new drug reduces symptoms by 30%, you click a link and watch the exact analysis run in your browser. The data processing, statistical tests, and visualizations execute in seconds using the same environment the authors used—preserved perfectly through reproducible containers.
Particularly the "data availability" and "Availability and peer review of computer code and algorithm".
However, in my limited experience, of trying to reproduce certain scRNA-seq processing pipelines, in practice it's never available as just a Github link. I can understand that some/many researcher's code is not in good shape, so I think it'll be quite a stretch to have this available.
I do think it's laudable though, to try and make it available. It would certainly have been very useful for me in the past.
Nice read. I believe that traditional software is a great way to showcase the proofs when it comes to physics and mathematics. You can easily code up a theorem in a language of your choice and justify that 'Okay, the output matches the expected value'.
I am particularly fascinated by labs like DeepMind [https://deepmind.google/science/]. The recent advances in their frontier models that are able to predict diseases before they're diagnosed is incredible. This is what AI should be built for and actually do!
> modern science is synonymous with open source software.
Another problem with reproducibility is the openness of the underlying data. Many academics are terrified of giving away the golden goose and the software is often useless without the data.
However many scientists do work openly, e.g. The Journal of Open Source Software:
> Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that".
TL;DR I claim that modern science is synonymous with open source software. This post explains why, why it matters, and what you can (and should) do next.
Equivalent? In the analogy of the math or physics results it would be a mental model in someone's brain that you can't access or verify. You just hope it's true
You argue that open software is science, which is not at all the same as claiming that science is software. ("is" in this context is not equivalence -- "a poodle is a dog" != "a dog is a poodle".)
I agree the post is muddy about whether the relationship is bijective (equivalent, poodle=dog) or injective (onto, poodle is a dog).
I make it slightly more precise in the statement "I posit that open source software is a necessary condition if we are to science in a computerized world". That's where the "is" comes from in the title. Throughout history, this definitely has not been the case. I'm arguing that's changing.
It's not just "muddy", it's thoroughly inconsistent and impenetrable (which probably has a lot to do with why there is so little engagement here). You say "TL;DR I claim that modern science is synonymous with open source software" which is radically different from your "slightly more precise" statement.
I won't put any more time into this ... good luck in figuring out what it is you really want to claim and presenting a coherent and cogent argument for it.
At least some journals have this as a stipulation e.g. https://www.nature.com/nature-portfolio/editorial-policies/r...
Particularly the "data availability" and "Availability and peer review of computer code and algorithm".
However, in my limited experience, of trying to reproduce certain scRNA-seq processing pipelines, in practice it's never available as just a Github link. I can understand that some/many researcher's code is not in good shape, so I think it'll be quite a stretch to have this available.
I do think it's laudable though, to try and make it available. It would certainly have been very useful for me in the past.
I am particularly fascinated by labs like DeepMind [https://deepmind.google/science/]. The recent advances in their frontier models that are able to predict diseases before they're diagnosed is incredible. This is what AI should be built for and actually do!
Another problem with reproducibility is the openness of the underlying data. Many academics are terrified of giving away the golden goose and the software is often useless without the data.
However many scientists do work openly, e.g. The Journal of Open Source Software:
https://joss.theoj.org/
> Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that".
I won't put any more time into this ... good luck in figuring out what it is you really want to claim and presenting a coherent and cogent argument for it.