

Things appear to have changed; thanks for drawing my attention to that. I may start editing some articles in my broader area.


Things appear to have changed; thanks for drawing my attention to that. I may start editing some articles in my broader area.


I can’t without doxxing myself more than I’d like. It wasn’t an article about himself, nor his research. This was about 10 years ago, so the rules may have changed. I’ll take a look and edit my post accordingly if so.


A problem with Wikipedia is that experts are not allowed to contribute to their areas of expertise because they’re “biased” (see edit below). I know a professor at a top university who used to spend his free time editing Wikipedia outside of his specific area but in his broad area of expertise as a method of disseminating science knowledge to the public. When the higher-up Wikipedia editors found out who he was, they banned his account and IP from editing.
Having the lay public write articles works when expertise isn’t required to understand something, but much of Wikipedia around science is slightly inaccurate at best. (This is still true, probably owing to the neutral point of view rule [giving weight to fringe ideas as a result] or the secondary source prioritization over primary sources.)
Edit: current Wikipedia editing rules and guidelines would not support this ban, so things appear to have changed. Wikipedia still recommends against primary sources as authoritative sources of information (recommending secondary sources instead), which is not great. But, they explicitly now welcome subject matter experts as editors.


Any NIH-funded research must be made open access one year after its publication date. NIH publishes the accepted manuscript in PubMed at the one-year mark. Unlike NIH, (last I checked) NSF doesn’t strictly require it, but you won’t be getting NSF funding unless you say you’re going to make the resulting papers freely available somehow (e.g., preprints, paying for open access, etc.). Not sure about DOE/DOD/etc. funded-articles.
The majority of federally funded research in the US is made open access. You might not realize it because news outlets typically report on brand-new articles, which haven’t hit the one-year mark for open access yet.


I didn’t struggle with any of it when I went through it, I just have subsequently found that I didn’t retain many of the rules. The derivative’s power rule is about the only rule I don’t have to look up these days. I’d like an online resource that has a bunch of practice exercises to help drill that stuff into me.


Can you link me some? I’d honestly really appreciate it. I’ve used Khan academy but it was too sparse on exercises
Edit: spelling


For learning calculus?
Honestly going to use this lol
Even somewhere warmer, I’m a 2 year-round, too. I just have one very cool sheet that I use in the summer.


Methods sections are limited in word count, and if a lab is hoping to get a few more papers out of a paradigm, they may be intentionally terse. There’s a big difference between how we write protocols in-house and how we write limited-length methods sections.


ONLYOFFICE (sorry about the caps, poor name choice IMO) has even better docx compatibility, and its source code is open


Trogdor was popular way before Reddit
Examples? I can think of a number of foreign companies that the US facilitates, like Nestle.


Eh, I switched. I switched all of my lab’s computers, too, and my PhD students have remarked a few different times that Linux is pretty cool. It might snowball.
I never understand why lemmy downvotes someone who is trying to help by providing accurate information, presumably because they think that there’s a very small chance that the person they’re replying to isn’t being sarcastic.


I was just in a smaller city in Germany and flew back to the US after that. I look German and speak German. When paying with card, Germany felt exactly like the US. At every restaurant, the tip request automatically came up within the thing used to process your card, just like in the US.
Recently, a company called Pangram appears to have finally made a breakthrough in this. Some studies by unaffiliated faculty (e.g., at U Chicago) have replicated its claimed false positive and false negative rates. Anecdotally, it’s the only AI detector I’ve ever run my papers through that hasn’t said my papers are written by AI.