@juulia.bsky.social
Your friendly neighbourhood (data & neuro-) scientist. Interested in healthcare, big data, social interaction, tea, and cats. ๐ซ๐ฎ living in ๐ธ๐ช
So the picture will be stretched over 2 pages, am I reading that right? with a few lines at the end for legend
06.02.2026 16:29 โ ๐ 2 ๐ 0 ๐ฌ 0 ๐ 0Thanks for a really interesting paper! I would love to take a look at the supplementary material but I can't figure out how to access it. Is that a separate file somewhere? If yes, would you be kind enough to share the link? ๐
05.02.2026 14:07 โ ๐ 1 ๐ 0 ๐ฌ 1 ๐ 0After 5 years of data collection, our WARN-D machine learning competition to forecast depression onset is now LIVE! We hope many of you will participateโwe have incredibly rich data.
If you share a single thing of my lab this year, please make it this competition.
eiko-fried.com/warn-d-machi...
It looks like that thatโs how the 150 circle (โmeaningful contactsโ) of Dunbarโs number is inofficially defined, I must have picked it up from there..
27.12.2025 11:55 โ ๐ 1 ๐ 0 ๐ฌ 0 ๐ 0I tend to go by: if I saw them sitting alone in a cafe or a bar, would I go join them or would I find a table of my own? Works for online folks but also imposes some limit of how much I need to like that person in order for them to โcountโ. I suspect that that limit scales with introversion though
27.12.2025 11:51 โ ๐ 1 ๐ 0 ๐ฌ 1 ๐ 0I went to Metallica gig with a group of professors and, I mean, they werenโt active participants in the mosh pit but they were *right* next to it. yes, theory was discussed.
10.12.2025 18:51 โ ๐ 1 ๐ 0 ๐ฌ 0 ๐ 0A photo of a woman in front of a large presentation. On the slide she's presenting, it says The new paradigms Joy has business value Get rid of dumb work If you can't get rid of the work, make computers do the work Don't make humans tell the computer things the computer already knows Get rid of flab from the programming model Measure the important metric, not the one that's easy to measure
Great talk by @hollycummins.com at Lindholmen developer day. As a data person and as someone who used to work with healthcare this resonated a lot: "don't make human tell computer things the computer already knows". It is so key but so often neglected in practice (&definitely a thief of joy) #databs
22.10.2025 08:05 โ ๐ 7 ๐ 3 ๐ฌ 0 ๐ 0Hahaha, ok so it's an avalanche of spam and very little ham it sounds like. That sounds better than the inverse to me actually ๐
08.10.2025 15:23 โ ๐ 0 ๐ 0 ๐ฌ 1 ๐ 0My best tip is to be very ruthless in having rules for email that automatically gets cleaned out of the inbox, e.g. automatic emails from systems, stuff that gets sent out as FYI, weekly XYZ digests etc. They all go into their own folders and I look at them if/when I feel like it. Maybe never.
08.10.2025 11:59 โ ๐ 0 ๐ 0 ๐ฌ 1 ๐ 0In my old job I would get around 20-30 emails per day that required me specifically to react to them (so, no automated emails, no mailing list stuff). In my new job, so far โจalmost nothingโจ. But I think email volume is likely a function of your tenure and/or network centrality in an organisation.
08.10.2025 11:56 โ ๐ 0 ๐ 0 ๐ฌ 2 ๐ 0Thank you everyone for your suggestions! This is how I ended up plotting my LLM system output vs human annotation vs LLM-as-a-judge evals. Extra thanks to @libbyheeren.bsky.social for boosting my original question. #databs #dataviz
08.10.2025 11:52 โ ๐ 3 ๐ 0 ๐ฌ 1 ๐ 0Wow, thank you so much @thoughtfulnz.bsky.social ! That's really pretty & so nice of you to make up a toy example! ๐คฉ๐คฉ๐คฉ
01.10.2025 07:32 โ ๐ 1 ๐ 0 ๐ฌ 0 ๐ 0Ooh, that's a thought! Thanks! I think it's good for the audience to have a sense of how prevalent true vs faulty answers are, but that doesn't necessarily need to be in the same plot as the comparisons ๐ค
30.09.2025 11:41 โ ๐ 0 ๐ 0 ๐ฌ 1 ๐ 0Thanks Libby! Something like this is what I'm leaning towards but with four sections (so that I can show false positives and false negatives separately, they have different business implications)
30.09.2025 06:17 โ ๐ 0 ๐ 0 ๐ฌ 2 ๐ 0Fair point! Right now I'm just going : right answer is the one a human gave + false positives and false negatives have different cost (false negatives are much more costly than false positives)
30.09.2025 06:16 โ ๐ 1 ๐ 0 ๐ฌ 0 ๐ 0Oh hey thanks, I hadn't really thought of radar plot for this! That's definitely worth considering!
30.09.2025 06:13 โ ๐ 1 ๐ 0 ๐ฌ 1 ๐ 0I think the problem is that data science is >10% thinking and you can't really externalize the thinking, just the execution. And even for execution you need to split in suitable sized chunks that you quality control yourself.
30.09.2025 06:12 โ ๐ 2 ๐ 0 ๐ฌ 1 ๐ 0Iโm really loving it for making and tweaking plots where I kind of know the plotting library but not well enough to remember all the functions and params by heart. @hadley.nz had a wonderful demo of this at the Posit conf earlier this month, it might be on youtube soon!
29.09.2025 19:46 โ ๐ 3 ๐ 0 ๐ฌ 2 ๐ 0Maybe sometime down the line! Right I have a number of evals coming from many different models & frameworks and need to figure out how to best visualize them for our dev team.
29.09.2025 14:25 โ ๐ 0 ๐ 0 ๐ฌ 0 ๐ 0Any references for good visualizations of LLM evals? We have orig system output (yes/no), a human annotator's y/n and a number of different y/n evaluations. The aim is to see how good our original system is and how much of the issues do the diff LLM evals catch. How would you visualize this? #databs
29.09.2025 14:10 โ ๐ 0 ๐ 0 ๐ฌ 5 ๐ 2My mentor once said: strongest results are the ones where you don't even need stats to figure out if there was an effect, you just plot the raw data and look at it with your two human eyes. If it's obvious then, it's a ding-dang strong effect.
24.09.2025 10:49 โ ๐ 3 ๐ 1 ๐ฌ 1 ๐ 0#DataBS Conf 2025 preshow! We have two talks that we couldn't fit into the schedule but the speakers pre-recorded their talk for us to share before the main event next week!
Both are really good and give me lots of excitement about what we'll see next week.
ti.to/databsconf/d... <- free tix
๐งต1/3
This week on Counting Stuff, the #dataBS conference attendee registration form is open! Also an intro to the 6 of 14 talks we have confirmed!
Tickets are free/pay-what-you-want and there's technically a limit on attendees so grab yours today!
www.counting-stuff.com/databs-conf-...
The weekend is here!
Perfect time to submit your #dataBS talk.
We want your lessons-learned stories from data work, everything from "my data pipeline: the unsung hero" to "how we got that AI system working" to "what we learned when it fell over."
Details and sign-up:
bit.ly/dataBSconf-cfs
Hi! Just wanted to let you know that there seems to be something wrong with the link - I get an 404 page when trying to open it and cant find the blog even in the blog tab.
18.07.2025 10:58 โ ๐ 0 ๐ 0 ๐ฌ 1 ๐ 0Hey #dataBS! Got some stories about how data is messily done to accomplish real things? Have you learned a painful lesson about how not to do something? Then you've got something to share and should submit a talk to the Data Behind the Scenes Conference! (Form closes July 31)
bit.ly/dataBSconf-cfs
The #dataBS (Data Behind the Scenes) Conference Call for speakers is out! We're gonna do this!!
All online, single track, free to attend. Come talk about your messy experiences doing data stuff. At work, personal projects, whatever. A space to commiserate about nerdy things!
bit.ly/dataBSconf-cfs
Academics, get thee some fuck off skills. Marketable skills that can help you fuck off from academia and get employed elsewhere. I see folx do multiple postdocs because they don't know what else they could do. Don't let that be you - make sure you have the ability to fuck off #academia #AcademicSky
05.06.2025 20:00 โ ๐ 16 ๐ 1 ๐ฌ 1 ๐ 2