#ChatGPT is being a very good sport playing "one of these things is not like the other" with pretty hopeless examples of four things. However, it is taking some amusing liberties with facts and logic. (1/2)
Explanation of the greenhouse effect by @skdh@nerdculture.de. Several plot twists so must watch to the end. https://www.youtube.com/watch?v=oqu5DjzOBF8
"Method for solving notorious calculus problems speeds particle physics computations"
https://www.science.org/content/article/method-solving-notorious-calculus-problems-speeds-particle-physics-computations
The basic story has been told before. In journals...
https://onlinelibrary.wiley.com/doi/full/10.1111/ina.13070
https://royalsocietypublishing.org/doi/full/10.1098/rsfs.2021.0017
...and in popular form:
https://www.wired.com/story/the-teeny-tiny-scientific-screwup-that-helped-covid-kill/
Lidia Morawska and 31 coauthors in a new article on the struggle to recognize #aerosol or #airborne transmission of #SarsCoV2. Maybe a scientific research journal is not the best place for this message but the topic is important.
https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciad068/7034152
@adam42smith Personally, I'm not looking for a full citation manager, but for a convenient way to add to my large, manually curated and carefully double-checked BibTeX file. I'd rather run a tiny command-line Python code than fire up a GUI for generating new BibTeX entries that I check and add information too before saving in my BibTeX file.
@adam42smith That's a pity because Zotero is really good in other ways and the browser button is brilliant.
@adam42smith That's a nice fix, thanks! How do I change export encoding in the web version?
@adam42smith As a quick example, using Zotero to generate a BibTeX entry for the article https://europepmc.org/articles/PMC8541564 gives me the author line
author = {Ružić Gorenjec, Nina and Kejžar, Nataša and Manevski, Damjan and Pohar Perme, Maja and Vratanar, Bor and Blagus, Rok},
The first name should have been written as Ru{\v z}i{\' c} in BibTeX. In my experience it's pretty random what you get---sometimes just the nearest accent-less/umlaut-less character, sometimes like this example, sometimes the correct BibTeX formatting. But one must always double check the Zotero output.
All #bibliographic tools I know (#Zotero, Papers, #CiteULike, etc.) do a terrible job with accents/umlauts and need to be hand corrected and I suspect this one is no different. However, it usually takes a few clicks on a journal webpage to get a #BibTeX entry. This program is at least as convenient and lends itself to automation.
This Python program for looking up a DOI and printing a #BibTeX entry looks useful:
Found an interview with the lead author of the #Cochrane review. He is a good example of someone engaging in default thinking:
"[...] it's a complete subversion of the ‘precautionary principle’ which states that you should do nothing unless you have reasonable evidence that benefits outweigh the harms."
https://maryannedemasi.substack.com/p/exclusive-lead-author-of-new-cochrane?utm_campaign=post
In the summer 2021, I collected a lot of literature on this and wrote up some thoughts. Much of it applies to the reception of the latest #Cochrane's summary too.
https://intemittdefault.wordpress.com/2021/07/10/evidence-decisions-and-default-reasoning/
(3/n, n=3)
Based on what I have seen during the pandemic, many people poorly equipped to interpret this sort of selective summary because they rely on a type of default thinking:
Pick a hypothesis that wins by default (e.g. a specific physical intervention is harmful/non-beneficial). Then once new studies become available, check if they give a strong and rigorous enough reason to reject the default; if not, keep the default. (Similar to how, in a court of law, the accused is by default innocent until proven beyond reasonable doubt to be guilty.)
This can be contrasted with a more Bayesian way of thinking:
No hypothesis wins by default. Decide on some initial degree of belief in a hypothesis and its negation. Carefully weigh new evidence for an against and incrementally update the degrees of belief. (2/n)
computational scientist, interested in science, news, politics