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: Social distancing is crucial for preventing the spread of contagious illnesses such as COVID-19 (coronavirus). COVID-19 can spread through coughing, sneezing and close contact. By minimizing the amount of close contact we have with others, we reduce our chances of catching the virus and spreading it to our loved ones and within our community.

Abstract:
The coronavirus disease (COVID-19) affecting across the globe.
The government of different countries has adopted various policies to contain this epidemic and the most common were social distancing and lockdown.
We use a simple log-linear model with intercept and trend break to evaluate whether the measures are effective preventing/slowing down the spread of the disease in Turkey.
We estimate the model parameters from the Johns Hopkins University (2020) epidemic data between 15th March and 16th April 2020.
Our analysis revealed that the measures can slow down the outbreak.
We can reduce the epidemic size and prolong the time to arrive at the epidemic peak by seriously following the measures suggested by the authorities.
{"verdict": "NEI", "evidence": []}