United States National Research Council and the National Council on Radiation Protection and Measurements and the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) argue that there is no evidence for hormesis in humans and in the case of the National Research Council hormesis is outright rejected as a possibility. Therefore, estimating Linear no-threshold model (LNT) continues to be the model generally used by regulatory agencies for human radiation exposure. Proposed mechanism and ongoing debate Radiation hormesis proposes that radiation exposure comparable to and just above the natural background level of radiation is not harmful but beneficial, while accepting that much higher levels of radiation are hazardous. Proponents of radiation hormesis typically claim that radio-protective responses in cells and the immune system not only counter the harmful effects of radiation but additionally act to inhibit spontaneous cancer not related to radiation exposure. Radiation hormesis stands in stark contrast to the more generally accepted linear no-threshold model (LNT), which states that the radiation dose-risk relationship is linear across all doses, so that small doses are still damaging, albeit less so than higher ones. Opinion pieces on chemical and radiobiological hormesis appeared in the journals Nature and Science in 2003. Assessing the risk of radiation at low doses (<100 mSv) and low dose rates (<0.1 mSv.min−1) is highly problematic and controversial. While epidemiological studies on populations of people exposed to an acute dose of high level radiation such as Japanese atomic bomb survivors () have robustly upheld the LNT (mean dose ~210 mSv), studies involving low doses and low dose rates have failed to detect any increased cancer rate. This is because the baseline cancer rate is already very high (~42 of 100 people will be diagnosed in their lifetime) and it fluctuates ~40% because of lifestyle and environmental effects, obscuring the subtle effects of low level radiation. Epidemiological studies may be capable of detecting elevated cancer rates as low as 1.2 to 1.3 i.e. 20% to 30% increase. But for low doses (1–100 mSv) the predicted elevated risks are only 1.001 to 1.04 and excess cancer cases, if present, cannot be detected due to confounding factors, errors and biases. In particular, variations in smoking prevalence or even accuracy in reporting smoking cause wide variation in excess cancer and measurement error bias. Thus, even a large study of many thousands of subjects with imperfect smoking prevalence information will fail