See for yourself:
Is it more like some new outcome like 'ohh, there's new method by which the cell would know the radiation doses at low near background level, even for alpha particles a single of which does giant damage! Some new exciting physics discovered - the quantum probability can be measured before event happens!. That got to be useful for something, maybe for defence response. Ohh, there is the defence response, and its so strong.... I wonder if low doses of radiation are good for you?'
Or is it more like like 'okay, suppose the radiation is good for you, let's think and come up with justifications, okay, the untapped powers of organism that will be'.
The former is the process of scientific enquiry, the latter is the process of pseudoscience - start with desired effect, make up vague cause, later on perhaps think up a zillion specific causes, good luck proving them all wrong. I wonder why we even take obvious products of entirely backwards reasoning at face value as if they were not fundamentally different from products of forward reasoning?
Also try calculate how many people are required to find LNT-predicted dose effects at 10x the background. There aren't going to be direct evidence. There will be very strong indirect evidence, such as difficulty for the cell to measure doses near background, and generally low prior probability for some magical untapped powers of organism.
I have seen for myself. And I've also read about all the other hormesis effects like cold, caloric restriction intermittent fasting, exercise etc, which make a potential hormetic effect from radiation quite plausible (regardless of your sarcasm about 'magical untapped powers').
I wonder why we even take obvious products of entirely backwards reasoning at face value as if they were not fundamentally different from products of forward reasoning?
I don't think it's backwards at all.
You're a very dismissive person, I think. I give you a link with all sorts of modern results and mechanisms, and all you do is speculate wildly about ulterior motives.
Nutrition is a case where we have to try to make the best possible use of the data we have no matter how terrible, because we have to eat something now to sustain us while we plan and conduct more experiments.
I want to apply Bayes theorem to make rational health decisions from relatively weak data. I am generally wondering how one can synthesize historical human experiences with incomplete scientific data, in order to make risk-adverse and healthy decisions about human nutrition given limited research.
Example question/hypothesis: Does gluten cause health problems (ie exhibit chronic toxicity) in non-coeliac humans? Is there enough evidence to suggest that avoiding gluten might be a prudent risk-adverse decision for non-coeliacs?
We have some (mostly in vitro) scientific data suggesting that gluten may cause health problems in non-coeliac humans (such as these articles http://evolvify.com/the-case-against-gluten-medical-journal-references/). Let's say for the sake of arguing, that I can somehow convert these studies into a non-unity likelihood ratio for gluten toxicity in humans (although suggestions are welcome here too).
However, we also have prior information that a population of humans has been consuming gluten containing foods for at least 10,000 years, without any blatantly obvious toxic effects. Is there some way to convert this observation (and observations like this) into a prior probability distribution?