Well, a quick search on InspireHEP shows a 2019 paper [1] that adds on Shaposhnikov and Wtterich's. Of note is that an updated top mass value changes the Higgs mass prediction to 132 GeV, rather in tension with 125 GeV. (The paper then cleverly tries to extend the Standard Model to adjust the prediction back to the measured Higgs mass.) The original argument doesn't look like such a slam dunk anymore.
[1] Kwapisz, "Asymptotic safety, the Higgs mass and beyond the Standard Model physics"
Prediction: https://arxiv.org/abs/1112.1059 Review and discussion: https://arxiv.org/abs/1211.2231
That being said, I still believe that asymptotic safety in quantum gravity is a really cool idea and it's well worth pursuing. It deserves better than to be used as a hammer for people bashing other legit science.
A prediction for the weight of Higgs boson particle using this, and it came true.
There is no shame in shining a bit of light on your own value. Just don’t make it blazing sun pointing at a small accomplishment.
It follows that shining light on value should be a shared responsibility. It’s not just the creator that’s negatively impacted when we fail to do so. We all are.
And of course, many binary segmentations work well for most cases and fail in unusual cases that can generally ignored.
People who take the credit are, almost by definition, competing with each other.
My observation is simply that giving credit to community-minded scientists costs nothing, but giving credit to psychopaths with the Kings ear can cost everyone their lives. There are always problems with a Meritocracy, as someone eventually has to define what has merit.
I am thankful to have goldfish crackers and jellybeans. Have a wonderful day =)
Sure this is shocking news, but hardly surprising given the shift in behavior of late. =)
Or find somewhere that operates differently. Some people hope that academia will be different and better than business. From what I can see it is often worse, but ymmv.
I'd explain why your informal fallacy is off-topic, but am rather focused on goldfish crackers and jellybeans at the moment.
Have a Gloriously wonderful day =)
Also, goldfish crackers... nom... nom... nom...
Have a great day, and no more hints. =P
Consider this toy example: The mass m is calculated from some parameter like m~=b^4 and that parameter b was measured b=2.0±0.1. Using Gaussian error propagation, m would be 16±3.2. Now update the measurement of b just slightly to b=2.1±0.05. That 5% change in b changes the result to m=19.45±1.85 -> more than 20%, and with just one standard deviation of difference in b. The relationship is not linear.