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:

Source apportionment of trace element pollution in surface sediments using positive matrix factorization combined support vector machines: application to the Jinjiang River, China. In this study, a method of positive matrix factorization (PMF) combined support vector machines (SVMs) was adopted to identify possible sources and apportion contributions for trace element pollution in surface sediments from the Jinjiang River, Southeastern China. Utilizing diagnostics tools, four significant factors were extracted from sediment samplers, which were collected in December 2010 at 15 different sites. By treating source identification as a pattern recognition problem, the factor loadings derived from PMF were classified by SVM classifiers which have been trained and validated with fingerprints of eight potential source categories. Using SVM, industrial wastewater from lead ore mining and metal handcraft manufacture, atmospheric deposition, and natural background were identified as main sources of trace element pollution in surface sediments from the Jinjiang River, which were affirmed by visually comparing compound patterns and the differences between the predicted and actual fractional compositions. Apportionment results showed that source of lead ore mining made the largest contribution (33.62 %), followed by atmospheric deposition (30.99 %), metal handcraft manufacture (30.09 %), and natural background (5.29 %).
{"Chemical": []}