The Hill has published some more information:
The state health department identified 469 COVID-19 cases among Massachusetts residents who went to Provincetown, a popular vacation destination in Barnstable County, in the month of July, including 346 fully vaccinated people.
Some 127 COVID-19 samples from the fully vaccinated, including recipients of all three U.S.-authorized vaccines, showed a similar viral load to the samples from the 84 unvaccinated people.
The report noted that microbiological studies are needed to confirm that similarity in the viral load to determine whether fully vaccinated people can transmit the virus.
I still have the impression that this data could be systematically biased: it makes sense that the viral load would be high among identified cases, but randomized testing of the broader population is needed to understand the base rates.
The CDC's claim that vaccinated people have similar viral loads from Delta as unvaccinated people is now spreading far and wide on social media. The Washington Post obtained their internal slide deck here, with the unpublished data supporting this claim on slide 17.
Does anyone understand how to square this with various other studies from the past few months with more positive results for vaccine efficacy, serum neutralization, etc.? Or even better, does anyone have the actual source for this data? To me, this claim seems too extreme to be likely, but even my many PhD scientist friends mostly seem to be accepting this completely uncritically.
"Twiki" is already the name of a wiki-related product (https://twiki.org/), so that might be confusing.
There was a correlation if she plotted the high-traffic times to the incidents … No. This was wrong. She was looking at it the wrong way. They didn’t just need to look at when things had happened. They needed to look at all the times Medina had seen similar conditions—high traffic, large-mass ships, mistuned reactors—and nothing had gone wrong.
– Naomi Nagata in "Babylon's Ashes" by James S. A. Corey
A few brief supplements to your introduction:
The source of the generated image is no longer mysterious: Inceptionism: Going Deeper into Neural Networks
But though the above is quite fascinating and impressive, we should also keep in mind the bizarre false positives that a person can generate: Images that fool computer vision raise security concerns
Zvi is their CEO.
I find their site on the wayback machine as recently as March 22, 2015. OP could also try PMing user:Zvi.
My view of nutrition is basically option 2. "Nutrition science" as it exists today seems to be primarily an attempt to study subtle, complex effects using small, poorly-controlled samples. There are basic facts about nutrients that are fairly well supported, but I have never become convinced of the superiority of any "diet" based on the supposed evidence for it.
That order is based on the increasing size of the sets of possible values, of course.
Is there a way to do this without needing to secure collateral for the refund, using some stable investment vehicle like a CD? "The earlier you pledge, the bigger refund you get if the contract isn't fully funded" might help avoid the "waiting until the last moment" issue, but maybe there's some perverse incentive or other blocker.
I'm also very curious about how this method could solve issues with funding of scientific research. The lack of market pricing for research is a major impediment to allocating public funds effectively. But what prediction market can accurately estimate the price of something that might not pay off for 100 years?