Tootfinder

paint() your data when you print them to make them easier to grasp: #rstats #console

GitHub - MilesMcBain/paint: paint the data
paint the data. Contribute to MilesMcBain/paint development by creating an account on GitHub.

Onze accountants in Nederland.....
"Volgens de Autoriteit Financiële Markten (AFM), die nauw met de Amerikaanse waakhond samenwerkte, hebben honderden medewerkers van Deloitte, PwC en EY vijf jaar lang gefraudeerd bij het maken van examens."
https://www.…

Accountantskantoren Deloitte, PwC en EY krijgen miljoenenboetes
Accountantskantoren Deloitte, PwC en EY zijn voor miljoenen beboet vanwege examenfraude. De Amerikaanse toezichthouder PCAOB heeft Deloitte en PwC een boete op van 3 miljoen dollar (zo'n 2,6 miljoen euro) en EY een boete van 2,5 miljoen dollar (ongeveer 2,15 miljoen euro) opgelegd.

🇺🇦 Auf radioeins läuft...
Miles Kane:
🎵 Love Is Cruel
#NowPlaying #MilesKane
#newRelease 🆕 single
https://mileskane.bandcamp.com/track/love-is-cruel
https://open.spotify.com/track/0u7sy3s6Wu2VrYwqub4Rp2

Met dank aan CDA, VVD, BBB, JA21, FvD en SGP riskeert Nederland ruim een half miljard euro mis te lopen door schrappen CO2-belasting.
Had je best wat leuke vergroeningsplannen voor de industrie van kunnen financieren...

Nederland riskeert boete van ruim half miljard euro bij schrappen CO2-belasting
Met de opdracht aan het kabinet om de CO2-heffing voor industrie af te schaffen, riskeert de Tweede Kamer dat Nederland een Europese boete van maximaal 600 miljoen euro moet betalen. Nederland had de belasting beloofd in ruil voor geld uit het coronaherstelfonds. De rol van VVD en CDA is pikant: zij waren voorstander van strenge voorwaarden.

Suojeltujen metsien määrä kasvaa tilastoissa, vaikka käytännössä mikään ei muutu #luonto

Suojeltujen metsien määrä kasvaa tilastoissa, vaikka käytännössä mikään ei muutu
Metsähallitus listasi yli miljoonan hehtaarin edestä valtion mailla sijaitsevaa metsää, jonka voisi ottaa tavanomaista luonnonsuojelua kevyemmän ”monimuotoisuutta tukevan hoidon” piiriin.

Voorstel AI fabriek(je) in Groningen. Een eerste bescheiden stap, investering van 130 miljoen euro, nog lang niet genoeg.
https://www.tweedekamer.nl/kamerstukken/brieven_regering/detail?id=2025Z13447&did=2025D30395

To give some examples:
When police get vastly differential results at investigating crimes against some groups (e.g., Black women) vs. others (e.g., white men), that's malcompetence. Probably plenty of simple malice involved too, and probably the whole gamut of mechanisms I mentioned in the last post are involved here.
Another example, from my own experience: when I stumble over the names of my non-white students but pronounce my white students' names flawlessly, that's malcompetence on my part, because the net effect of my selective incompetence is to make some students feel less welcome in my classroom, which hurts their learning. I'm my case, the reasons for the incompetence are not conscious nor (I think) unconscious malice, but instead a differential capability picked up from a certain kind of upbringing and then (sometimes) insufficiently mitigated by capability-building effort. Because of how I grew up, my ability to pronounce different names is biased (this is true of everyone in the world; most people don't have a classroom instructor position that causes it to matter so much). When I'm successful at mitigating my malcompetence, I use practice time with student intro videos to pare down my competence gap for the specific students in my class. This is time consuming (several hours per week for the first few weeks of classes) and I'm sad to admit that I don't always invest that time. But it's a great example of malcompetence because I have a introspective access to it.

CT Radiomics-Based Explainable Machine Learning Model for Accurate Differentiation of Malignant and Benign Endometrial Tumors: A Two-Center Study
Tingrui Zhang, Honglin Wu, Zekun Jiang, Yingying Wang, Rui Ye, Huiming Ni, Chang Liu, Jin Cao, Xuan Sun, Rong Shao, Xiaorong Wei, Yingchun Sun
https://arxiv.org/abs/2506.18106

CT Radiomics-Based Explainable Machine Learning Model for Accurate Differentiation of Malignant and Benign Endometrial Tumors: A Two-Center Study
Aimed to develop and validate a CT radiomics-based explainable machine learning model for diagnosing malignancy and benignity specifically in endometrial cancer (EC) patients. A total of 83 EC patients from two centers, including 46 with malignant and 37 with benign conditions, were included, with data split into a training set (n=59) and a testing set (n=24). The regions of interest (ROIs) were manually segmented from pre-surgical CT scans, and 1132 radiomic features were extracted from the pr…

Who will Raiders prioritize of their pending free agents? https://www.reviewjournal.com/sports/raiders/who-will-raiders-prioritize-of-their-pending-free-agents-3390235/

Easier debugging of piped analyses in R: https://github.com/MilesMcBain/breakerofchains by @…