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: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. 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:

The impact on productivity of a hypothetical tax on sugar-sweetened beverages To quantify the potential impact of an additional 20% tax on sugar-sweetened beverages (SSBs) on productivity in Australia. We used a multi-state lifetable Markov model to examine the potential impact of an additional 20% tax on SSBs on total lifetime productivity in the paid and unpaid sectors of the economy. The study population consisted of Australians aged 20 years or older in 2010, whose health and other relevant outcomes were modelled over their remaining lifetime. The SSBs tax was estimated to reduce the number of people with obesity by 1.96% of the entire population (437,000 fewer persons with obesity), and reduce the number of employees with obesity by 317,000 persons. These effects translated into productivity gains in the paid sector of AU$751 million for the working - age population (95% confidence interval: AU$565 million to AU$954 million), using the human capital approach. In the unpaid sector, the potential productivity gains amounted to AU$1172 million (AU$929 million to AU$1435 million) using the replacement cost method. These productivity benefits are in addition to the health benefits of 35,000 life years gained and a reduction in healthcare costs of AU$425 million. An additional 20% tax on SSBs not only improves health outcomes and reduces healthcare costs, but provides productivity gains in both the paid and unpaid sectors of the economy.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["obesity"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["improves", "examine"], "Food": ["sugar-sweetened beverages", "SSBs"], "HealthCareActivity": [], "InjuryOrPoisoning": [], "IntellectualProduct": ["replacement cost method", "multi-state lifetable Markov model"], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["study population", "Australians", "population", "persons", "people", "older"], "ProfessionalOrOccupationalGroup": ["employees"], "ResearchActivity": ["modelled"], "SpatialConcept": ["Australia", "approach"], "Virus": []}