I'm sorry, theory's great and all, but I'm not interested. Call me when you see this in water not dreamed up in silico, okay? Yeah, I know, supercritical is hard, but... that's kind of the point, yeah? Why trust your model if we know this stuff is hard? Why care if it can never be realized? (Okay, you got me, I'm a constructivist too.)
(Must every press release by a British university be trash?)
> Call me when you see this in water not dreamed up in silico, okay?
The article, surprisingly was pretty clear about this. The headline? Pretty sensationalist.
> (Must every press release by a British university be trash?)
This has been the bane of science for as long as science has been around: How do you take something that isn't particularly interesting to laypersons and help them understand how important this little micro-bit of progress might be... on not be... It's hard.
> This has been the bane of science for as long as science has been around: How do you take something that isn't particularly interesting to laypersons and help them understand how important this little micro-bit of progress might be... on not be... It's hard.
I mean, I've seen my own work go through the Science News Cycle ( https://phdcomics.com/comics/archive.php?comicid=1174 ). I know what it's like. I'm just pointing out that British universities have a reputation for being absolutely terrible about this, to the degree that there's no point trusting a single thing their PR departments say anymore.
It seems the article extremely clearly communicates (as your plentiful quotes aptly demonstrate) that the evidence in question is a computational model.
I do not get your point about this being bad science communication at all. Your own quotes demonstrate that the press release is crystal clear about the type of evidence.
Your beef is with the science, not the communication. And you shouldn’t mix those two up.
> Your beef is with the science, not the communication. And you shouldn’t mix those two up.
No, my beef is that communicating this was irresponsible because it does not represent meaningful progress in an accurate understanding of the physics of water, and thus no impression should be given that it does.
Science grows through communication. The two are not separable.
I am someone that regularly rails against in silico work, but come on. Treat this as a sanity check to start understanding
1. if the colloidal thought model explains unexplained observables
2. If the colloidal model makes predictions not observed yet.
It might be too harsh to say this is not a meaningful advance. The system may be too difficult to make predictions without a computer, so having a thought model is useless. Now that we have a computer model, we can start doing experimental work that we wouldn't have chosen to do otherwise.
There is no evidence here. There is a model of water that apparently does something. Like FIFA22 (the game) is a model of the football (soccer) teams. But the model doesn't mean this can be translated to reality.
And at least with FIFA22 you can check against reality for accuracy!
But we live inside a computer, didn’t you know that? That the Universe itself is one big computer (and physics is computation)? A 42-bit one, unlike your fancy laptops…
> computer simulations
> model
> model
> computational work
> computational evidence
> colloidal model
I'm sorry, theory's great and all, but I'm not interested. Call me when you see this in water not dreamed up in silico, okay? Yeah, I know, supercritical is hard, but... that's kind of the point, yeah? Why trust your model if we know this stuff is hard? Why care if it can never be realized? (Okay, you got me, I'm a constructivist too.)
(Must every press release by a British university be trash?)