Nicola Romanò @nicolaromano@qoto.org

As PhD student, I only have little experience in being a reviewer in #PeerReview. But I always try to give concrete suggestions for improving unclear sections/sentences/missing information. Being concrete helps to be modest and keep away the idea that there is an 'ideal text' somewhere in my mind (to which my papers would never live up either).
However, this could be a different story if I had to do a review per week...

PSA, if someone asks you for contact info (e.g. a phone number) of someone you know, the correct response is "I can't give that to you, but I can give them yours".

It's efficient and adds no round-trips, it's privacy friendly, it's non-awkward and it's social engineering resistant. It's a universally good rule.

And the corollary, of course: Don't ask someone for another person's contact info - ask them to pass on yours.

Am I misunderstanding something?

This appears to be a stunningly irresponsible story in Science, claiming that up to 30% of the scientific literature is fake.

https://www.science.org/content/article/fake-scientific-papers-are-alarmingly-common

Below, the first two paragraphs of the story.

h/t @Hoch

I've always been very proud to have a very diverse lab. I think this picture of our names in different languages sums it up nicely. Note it's an incomplete list because not all members were present (we would also have vietnamese).

Finally, a solution to the unfairness of authorship ordering in scientific papers! 😂

"Every Author as First Author"

https://arxiv.org/abs/2304.01393

A pre-LLM snapshot of Wikipedia — frozen, meaning no new edits, you know, like an encyclopedia — would be a good thing. Because of course Wikipedia will be the number one target for people and forces trying to build fake legends.

https://xoxo.zone/@fraying/110328251695008281

It sounds trivial and obvious, but are you reading error bars correctly?

Do you know whether you're looking at standard errors (measures of inferential uncertainty), standard deviations (measures of spread of individual observations), or 95% confidence intervals around the mean?

And are your intuitions about what each of these mean correct?

Here's a nice primer, refresher, or teaching article.

https://www.nature.com/articles/nmeth.2659

h/t @jakehofman

Inspired by Kate Raworth's Doughnut Economics, Anne Urai and Clare Kelly imagine an ‘academic doughnut’ for rethinking academia for climate action.

🎧 Listen in the #eLifePodcast
https://elifesciences.org/podcast/episode86?utm_source=mastodon&utm_medium=social&utm_campaign=organic

⚪ Ein Baumbild und ... ein
Lieblingsfoto. 🧐
🟤 A tree picture and ... a
favorite photo. 🌳
📷 by Artist: #EdselJamesBatuigas in Loc.: #BritishColumbia Canada 🇨🇦 - Title: "Hiding in plain sight." - #Streetart #Art #Mastoart #Owl
#Photography #Fotografie #Tree #Wildlive #Camouflage
➡️ #APhotoLove see you👋

The Guardian covers the story of the mass resignation of "Neuroimage" (published by Elsevier) editorial board.

https://www.theguardian.com/science/2023/may/07/too-greedy-mass-walkout-at-global-science-journal-over-unethical-fees

#elsevier #OpenAccess #Neuroscience #ScienceMastodon

Do you read people's profile info before you follow them? Please boost for a bigger sample size, because I'm really curious about this

Ok. So recently, #Tesla had published an "Impact Report" which contained a slide presenting some "data" that their #Autopilot and #FSDBeta products "enhance safety".

And one article and one Twitter thread caught my eye in scrutinizing these numbers.

https://www.forbes.com/sites/bradtempleton/2023/04/26/tesla-again-paints-a-very-misleading-story-with-their-crash-data/

https://twitter.com/NoahGoodall/status/1651323363099553793

While the analyses and arguments in this article and thread are not necessarily wrong, there are more fundamental issues here that need to be surfaced in my view... so let's take a look.

Me: Did you know that cars produce nitric oxide as they burn fuel

You: NO?

Me: Yeah nitric oxide.

#ChemistryJokes