1: that happens for quite significant doses only (1 centigray = 0.01 gray = 10 millisievert for gamma and x-rays = 1000 hours of exposure to 10 microsievert/hour background)
2: on single cell level there is no small doses, there's small probabilities of 1 particle track through nucleus (edit: or 1 Compton scattering electron track for gamma rays). Non-linear response to probability would indeed be quite extraordinary.
Ionization of DNA molecules is going to be linear in response to radiation, but you can't assume that will result in a linear cancer risk. Cells can up and down regulate their DNA repair mechanisms under varying conditions, allowing for a much more complicated relationship between radiation and cancer risk.
In this case, cells appear to up-regulate poly (ADP-ribose) polymerase (PARP) in response to past radiation exposure, increasing the chance of an accurate repair after an ionization event damages one strand.
//edit: The nucleus is also not the only potential site of cancer inducing mutations, the mitochondrial genome is another possibility.
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?