What I was getting at with the issue of credibility is that I (or most others) would have time determining if a particular scholarly author in pharma is a good person to listen to on the subject. But having evidence that Derek Lowe is an honest broker of information in that domain, given his long history of commentary as well as other chemists I know who eagerly read his commentary, I'm willing to defer to his assessment.

It's difficult to calibrate statements made by other scientists unless you're well embedded within a field: Is this someone whose opinions matter? Are they the subject matter expert they make themselves out to be? Is this research itself truly impactful? Is it really 5 years until it will be realized outside of academic labs? Etc...

It's difficult to decipher questions around credibility because they rely on real-world interactions and associations that extend beyond the physical tokens of paper counts, publication venues, citations, and author lists that typically lag behind the front of human knowledge which is generated from real-world interactions. It can be simple things, like the insightful question a grad student, with minimal publication history, asks in a seminar.

Of course, the paywall is also unhelpful too, but a good, brief commentary by an appropriate commentator is a better link for 99% of prospective readers compared to most "peer reviewed" (scare quotes because that's a real question nowadays) articles.

Naruto: https://floor796.com/#t2l4,684,675

The author continues adding and refining the project, so if it isn't in there yet, perhaps in the future.

Was it because you were male or because you were studying math? Many schools struggle to find good math teachers; it's one of the qualifications in perpetual shortage.

The author has never worked in chemistry. They are absolutely ubiquitous in scholarly journals for chemistry and I'd say that most people trained in chemistry often only read the graphical abstract when initially deciding whether the paper is worth a deeper read. Perhaps chemistry is a naturally visual field, given that we rely on visualizations of reactions and mechanisms from the very start of our university education.

The table of contents (TOC) graphic usually shows a key chemical structure (thus bonding connectivity, angles, elements, and electronic configurations), reaction mechanisms or conditions, models, or even core results as graphs. Now I do not claim to understand what is implied in every TOC graphic, however I can immediately see which branches of chemistry the article relates to faster than I can process the title, especially in a multidisciplinary chemistry journal.

That ability to categorize to identify relevance is a bigger issue in reading a multidisciplinary chemistry journal like the Journal of the American Chemical Society:

https://pubs.acs.org/toc/jacsat/current

But graphical abstracts are still immensely useful within a subdiscipline such as organic chemistry, which I suspect were the early adopters of TOC graphics:

https://pubs.acs.org/toc/joceah/current

The better graphical abstracts tend towards simplicity, but it's a challenging task to distill a year or more of research into a single picture. And, unfortunately, graphic design is not a subject for which scientists generally receive additional training, despite it being a core element of digital communication.

> One of the simplest approaches to correct for multiple testing is the Bonferroni correction. The Bonferroni correction adjusts the alpha value from α = 0.05 to α = (0.05/k) where k is the number of statistical tests conducted. For a typical GWAS using 500,000 SNPs, statistical significance of a SNP association would be set at 1e-7. This correction is the most conservative, as it assumes that each association test of the 500,000 is independent of all other tests – an assumption that is generally untrue due to linkage disequilibrium among GWAS markers.

https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...

cf: https://en.wikipedia.org/wiki/Bonferroni_correction

Comments URL: https://news.ycombinator.com/item?id=46117343

Points: 7

# Comments: 1

Suggestion: Most of the fits that you've done assume that the errors are normally distributed. It would be worthwhile adding some graphical or numerical checks on that, rather than having goodness of fit or visual inspection be the only indication if this is a faulty assumption.

It gave made for a good quick check testing some data I had.

As you noted, one needs a lot of fine tuning to meet publication rules & guidelines. Compared to a local LaTeX editor or Overleaf, this looks too generic to meet the needs I've had in the past. Sure, LaTeX can require a lot of tinkering, but PhD students ought be able to figure it out for themselves, whether through documentation, forums, or asking labmates.

- https://www.engadget.com/big-tech/youtube-may-reinstate-chan...

- https://arstechnica.com/gadgets/2025/09/youtube-will-restore...

The Globe and Mail had a piece on March 25th on the advice that lawyers were giving to their clients, often Canadians working on TN visas down south:

> York-based immigration law firm Dyer Harris LLP, which helps foreigners secure work visas in the U.S., sent an e-mail to their clients residing and working in the country to hold off on international travel altogether, unless in an emergency.

Lawyers advise Canadians working in U.S. to avoid travel amid border crackdown, The Globe and Mail, 2025-03-25. https://web.archive.org/web/20250325223021/https://www.thegl...

Comments URL: https://news.ycombinator.com/item?id=41712512

Points: 1

# Comments: 0