You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Another candidate vaccine, called CoronaVac , being developed by Beijing-based Sinovac Biotech, protected rhesus macaque monkeys from infection with the novel coronavirus,

Abstract:
The recent outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development.
Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cells via the HLA complex.
SARS-CoV-2 is a large RNA virus and testing of all overlapping peptides in vitro to deconvolute an immune response is not feasible.
Therefore HLA-binding prediction tools are often used to narrow down the number of peptides to test.
We tested 19 epitope-HLA-binding prediction tools, and using an in vitro peptide MHC stability assay, we assessed 777 peptides that were predicted to be good binders across 11 MHC allotypes.
In this investigation of potential SARS-CoV-2 epitopes we found that current prediction tools vary in performance when assessing binding stability, and they are highly dependent on the MHC allotype in question.
Designing a COVID-19 vaccine where only a few epitope targets are included is therefore a very challenging task.
Here, we present 174 SARS-CoV-2 epitopes with high prediction binding scores, validated to bind stably to 11 HLA allotypes.
Our findings may contribute to the design of an efficacious vaccine against COVID-19.
{"verdict": "NEI", "evidence": []}