I tried looking for the conclusion, but I think the journal article preview does not show it. AI being used for something doesn't mean it will be used to "tran

I tried looking for the conclusion, but I think the journal article preview does not show it. AI being used for something doesn't mean it will be used to "transform" something. Lots of things can block the adoption of new technology due to the bias of practitioners or entrenched policy of "that's the way things are done". Healthcare doesn't switch from using fax machines for lots of reasons. If BBC makes a giant leap that AI will "transform" biology, the burden is on them to hint at why biologists would find it reliable and accessible enough to warrant inserting it into their toolkits. How easy is the adoption of ML models in the hard sciences today? Lastly, I don't read many ML papers but as an outsider, the "Code Availability" section seems odd. It may be cut off from the article preview I saw, but is it possible to get access to a singular code base that the research used to generate results? The section's first few paragraphs are "here are the libraries we used"