You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

An appeal for the presentation of detailed human derived data for dose-response calculations in nutritional science. If a diet, food or food constituent is recognised to have both health benefits and health risks, the benefits have to be compared with the risks to develop coherent scientific evidence-based dietary advice. This means that both risk and benefit assessment should follow a similar paradigm and that benefits and risks are expressed in a common currency. Dose-response functions are vital for that purpose. However, the construction of these functions is often of second interest in the currently available (epidemiological) literature. In order to bring forward the potential of epidemiological studies for the construction of the dose-response functions for benefit-risk purposes, the scientific (nutrition and health) community is asked to expand on their data presentation, either by presenting more detailed data focusing on dose-response necessities, and/or by sharing primary data.
{"Chemical": []}